ABSTRACT

Turun kauppakorkeakoulu • Turku School of Economics

Bachelor´s thesis

x Master´s thesis

Licentiate´s thesis

Doctor´s thesis

Subject Operations & Supply Chain Management Date 4.6.2019

Author Mikko Harteela Student number 506577

Number of pages 85 + appendices

Title Distribution of environmental and social sustainability in supply chains:

Analysis of green and social bullwhip effects

Supervisor D.Sc. Sini Laari

Abstract

Stakeholder demands for environmentally and socially sustainable operations are at an all-time high

as the repercussions of global crises, such as climate change, are becoming clearer when business is

conducted “as usual”. By better understanding the distribution of sustainability in supply chains,

stakeholders could apply pressure on the least sustainable tiers of the chain.

Green bullwhip effect refers to the transformation of external stakeholder pressure to environmen-

tal requirements within a supply chain. Stakeholders exert pressure on the most visible company in

the downstream wherefrom each tier in the chain renders the requirements content- and implementa-

tion schedule-wise more stringent for the next-in-line to create a safety buffer or in anticipation of

future demands. Environmental requirements, as a result, are tightest at the upstream of the supply

chain. Green bullwhip effect has been studied to some extent, whereas possible social bullwhip effect

has been scarcely explored. Instead of environmental requirements, in the case of social bullwhip

effect, demands for social reforms are analogously magnified throughout the supply chain. These two

phenomena could shed light on sustainability patterns in supply chains.

Using environmental, social and corporate governance (ESG) data from 290 European companies

involved in manufacturing supply chains, analysis of variance was applied to test for statistically

significant differences between the group means, groups referring to different supply chain positions

and industries. Each company was given a supply chain position and an industry attribute to test the

distribution of sustainability between tiers, and between industries. Results support the existence of

both green and social bullwhip effect to some extent. Industry was discovered to have no effect on

sustainability. Results imply that stakeholders should turn their attention towards wholesale and retail

activities, as they perform the worst in comparison to other tiers in a supply chain, namely end product

manufacturers and raw material suppliers/component manufacturers.

Key words green bullwhip effect, social bullwhip effect, sustainability, stakeholder pressure

Further

information

VälivälTIIVISTELMÄ

Turun kauppakorkeakoulu • Turku School of Economics

Kandidaatintutkielma

x Pro gradu -tutkielma

Lisensiaatintutkielma

Väitöskirja

Tiivistelmä

Sidosryhmät vaativat yrityksiltä ympäristöllisesti ja sosiaalisesti kestäviä liiketoimintatapoja enem-

män kuin koskaan aikaisemmin tilanteessa, jossa maailmanlaajuisten kriisien kuten ilmastonmuutok-

sen vaikutukset näkyvät entistä selvemmin, kun liiketoimintaa jatketaan ”entiseen malliin”. Ymmär-

tämällä paremmin kestävyyden jakautumista toimitusketjuissa sidosryhmät osaisivat kohdistaa pai-

neistamistoimensa toimitusketjujen vähiten kestäviä tasoja kohtaan.

Vihreä piiskavaikutus tarkoittaa ulkoisen sidosryhmäpaineen muuntamista ympäristövaatimuk-

siksi toimitusketjun sisällä. Sidosryhmät painostavat toimitusketjun näkyvintä yritystä alavirralla,

jolta ympäristöllisesti kestävään liiketoimintaan tähtäävät vaatimukset kulkevat tasolta toiselle jokai-

sen tason kiristäessä joko vaatimusten sisältöä tai toteutusaikataulua. Tämä kiristys on seurausta toi-

mijoiden halusta varmistaa oma toimintansa luomalla varmuuspuskuri tai varautua uusiin vaatimuk-

siin kiristämällä vaatimuksia entisestään. Lopputuloksena nämä vaatimukset ovat tiukimmat toimi-

tusketjun ylävirralla. Vihreätä piiskavaikutusta on tutkittu jonkun verran, kun taas sosiaalista piiska-

vaikutusta ei käytännössä lainkaan. Sosiaalisessa piiskavaikutuksessa ympäristövaatimusten sijasta

vaaditaan sosiaalisia uudistuksia, joita tiukennetaan ympäristövaatimusten tavalla läpi toimitusketjun.

Varianssianalyysiä käytettiin tutkimusmenetelmänä tilastollisesti merkittävien erojen havaitse-

miseksi ympäristöllistä ja sosiaalista suorituskykyä mittaavien keskiarvojen välillä. Jokaiselle otok-

sen 290 eurooppalaiselle yritykselle määriteltiin ryhmäattribuutti toimitusketjusijainnin ja toimialan

mukaan. Tulokset tukevat vihreän ja sosiaalisen piiskavaikutuksen olemassaoloa varauksin. Toi-

mialalla ei havaittu olevan vaikutusta kestävyyteen. Tulosten mukaan sidosryhmien tulisi kohdistaa

paineistamistoimia tukku- ja vähittäismyyjiä kohtaan näiden valmistavia tasoja heikoimman ympä-

ristöllisen ja sosiaalisen kestävyyden vuoksi.

Asiasanat vihreä piiskavaikutus, sosiaalinen piiskavaikutus, kestävyys, sidosryhmäpaine

Muita tietoja

Oppiaine Toimitusketjujen johtaminen Päivämäärä 4.6.2019

Tekijä Mikko Harteela Matrikkelinumero 506577

Sivumäärä 85 + liitteet

Otsikko Ympäristöllisen ja sosiaalisen kestävyyden jakautuminen toimitusketjuissa:

Vihreä ja sosiaalinen piiskavaikutus

Ohjaaja KTT Sini Laari

DISTRIBUTION OF ENVIRONMENTAL

AND SOCIAL SUSTAINABILITY

IN SUPPLY CHAINS

Analysis of green and social bullwhip effects

Master´s Thesis

in Operations and Supply

Chain Management

Author:

Mikko Harteela

Supervisor:

D.Sc. Sini Laari

4.6.2019

Turku

The originality of this thesis has been checked in accordance with the University of

Turku quality assurance system using the Turnitin OriginalityCheck service.

Table of contents

1 INTRODUCTION ................................................................................................. 11

1.1 Background and motivation for the research ............................................... 11

1.2 Research questions & structure of the thesis ................................................ 14

2 DEMAND FOR ENVIRONMENTAL AND SOCIAL SUSTAINABILITY IN

BUSINESS ............................................................................................................ 15

2.1 Dawn of modern sustainability concept: triple bottom line ......................... 15

2.2 Criticism of triple bottom line ...................................................................... 16

2.3 Notions on sustainability in the academic realm .......................................... 19

2.4 Under pressure—a stakeholder perspective on sustainability ...................... 20

3 ENVIRONMENTAL AND SOCIAL SUSTAINABILITY MANAGEMENT &

MEASUREMENT ................................................................................................. 25

3.1 Green Supply Chain Management ............................................................... 25

3.2 Sustainable Supply Chain Management ....................................................... 26

3.3 From financial performance measurement to sustainability performance

measurement ................................................................................................ 28

3.4 Means of measuring sustainability ............................................................... 30

4 BULLWHIP EFFECT AND ITS EXTENSIONS ................................................. 33

4.1 Bullwhip effect encountered, recognised & popularised ............................. 33

4.2 Green take on the bullwhip effect ................................................................ 35

4.3 Social bullwhip effect—does it exist? .......................................................... 36

4.4 Supply chain position paradox ..................................................................... 38

5 HYPOTHESES DEVELOPMENT ....................................................................... 40

6 METHODOLOGY ................................................................................................ 43

6.1 Methodological approach ............................................................................. 43

6.2 Data source ................................................................................................... 45

6.3 Data collection & sampling .......................................................................... 48

6.4 Data analysis ................................................................................................ 50

6.5 Validity and reliability of the research ......................................................... 50

7 RESULTS .............................................................................................................. 52

7.1 Assumptions of ANOVA tests ..................................................................... 52

7.2 Results of hypotheses testing ....................................................................... 55

7.3 Results of post hoc tests ............................................................................... 58

8 CONCLUSIONS & DISCUSSION ....................................................................... 64

8.1 Discussion of the results ............................................................................... 64

8.2 Managerial implications ............................................................................... 68

8.3 Limitations and future research .................................................................... 70

REFERENCES ................................................................................................................ 72

APPENDIX 1 ESG ENVIRONMENTAL MEASURES LIST............................... 86

APPENDIX 2 ESG SOCIAL MEASURES LIST ................................................... 89

APPENDIX 3 SAMPLE COMPANIES, MANUFACTURER 1 SCP ................... 92

APPENDIX 4 SAMPLE COMPANIES, MANUFACTURER 2 SCP ................... 96

APPENDIX 5 SAMPLE COMPANIES, VENDOR SCP ....................................... 99

List of figures

Figure 1 Comparison of TBL how it was intended by Elkington, how TBL is

often implemented in practice and the ecologically dominant logic

leading to true sustainability ............................................................... 17

Figure 2 Layer cake model distinguishing the interdependence between

environmental, social and economic dimension ................................. 18

Figure 3 Business research methodologies of the Neilimo and Näsi framework

supplemented by Kasanen et al. ......................................................... 43

Figure 4 Visualisation of research approaches and main methods in the Arbnor,

Bjerke and Vafidis framework ........................................................... 44

Figure 5 Thomson Reuters ESG scoring .......................................................... 46

Figure 6 Division of SCPs utilised in this research, sample size

in parentheses ..................................................................................... 49

List of tables

Table 1 Testing the normal distribution assumption of data between groups . 53

Table 2 Testing the assumption of homoscedasticity with Levene’s test,

comparisons between SCPs ................................................................ 54

Table 3 Testing the assumption of homoscedasticity with Levene’s test,

comparisons between industries ......................................................... 54

Table 4 Results of ANOVA tests, distribution of environmental and

social sustainability between SCPs .................................................... 56

Table 5 Results of ANOVA tests, distribution of environmental and

social sustainability between industries.............................................. 57

Table 6 Post hoc test p-values for group mean comparisons between SCPs .. 58

Table 7 Post hoc test p-values for group mean comparisons,

process and light industries ................................................................ 60

Table 8 Post hoc test p-values for group mean comparisons, metal refining

and metal products and machines, appliances and

transport equipment industries ........................................................... 61

Table 9 Post hoc test p-values for group mean comparisons, computers and

electronics industry ............................................................................. 62

Table 10 Score differences between SCPs, workforce category excluded ........ 63

Table 11 Summary of hypotheses testing .......................................................... 67

List of abbreviations

ANOVA Analysis of variance

BSC Balanced Scorecard

CSPMS Corporate sustainability performance measurement system

CSR Corporate social responsibility

DJSI Dow Jones Sustainability Indices

ESG Environmental, social and corporate governance

GBE Green bullwhip effect

GEMI Global Environmental Management Initiative

GHG Greenhouse gas

GRI Global Reporting Initiative

GSCM Green supply chain management

IPCC Intergovernmental Panel on Climate Change

KPI Key performance indicator

LCSCM Low carbon supply chain management

MSCI Morgan Stanley Capital International

NGO Non-governmental organisation

SBE Social bullwhip effect

SCM Supply chain management

SCP Supply chain position

SM Sustainable manufacturing

SPMS Strategic performance measurement system

TBL Triple bottom line

TR Thomson Reuters

TRBC Thomson Reuters Business Classification

11

1 INTRODUCTION

1.1 Background and motivation for the research

Practices aiming at conducting business in a more environmentally and socially sustain-

able manner are currently unprecedentedly popular, and sustainability has been recog-

nised as a megatrend (Mittelstaedt et al. 2014). Although the emergence of sustainable-

minded business paradigm cannot be pinpointed to one specific moment in history, one

concept can be viewed to have acted as a catalyst for such development. This concept was

triple bottom line popularised by Elkington in 1994. Elkington introduced two new di-

mensions alongside the traditional economic approach for monitoring company perfor-

mance, environmental and social. (Elkington 2018.) What ensued was a growing interest

to study sustainable practices and to measure sustainability by different means in the ac-

ademic field.

Triple bottom line (TBL) incorporated all three elements of the “people, planet, profit”

triangle into one accounting paradigm in contrast to the traditional “single bottom line”

monitoring only financial performance of a company (Elkington 2004). The concept in

practice developed into green supply chain management (GSCM) and sustainable supply

chain management (SSCM), providing concrete tools for companies to embrace new ide-

als not solely revolving around turning a profit. GSCM refers to the integration of envi-

ronmental management to business activities. GSCM is implemented through different

practices which can be internal or external—internal ones have an effect in-house, such

as eco-design, while external practices target external stakeholders, e.g. requiring suppli-

ers to provide an environmental certification. (Srivastava 2007; Zhu et al. 2012.) Defini-

tion of SSCM often overlaps with the one of GSCM, but traditionally SSCM has also

incorporated the social dimension to business management. SSCM practices with a social

approach are, for example, participating in ventures within the local community of sup-

plier to improve living and working conditions. (Seuring & Müller 2008; Klassen & Ve-

reecke 2012.)

By implementing such modern sustainability practices, companies could e.g. reduce

their resource use, motivate employees to work more efficiently and gain access to certain

expertise of suppliers and customers in a supply chain and key resources offered by stake-

holders. Ultimately, competitive advantage is created, and new customer groups are at-

tracted, especially ethical consumers. (Wolf 2014.) Ethical products is an increasingly

important market which cannot be entirely neglected by manufacturing supply chains due

to its expanding size. According to Bezençon and Blili (2010, 1305) market of ethical

products where “consumers buy intangibility, justice and perhaps conscience, is challeng-

12

ing the common theories of consumer rationality”. Ethical products are described to pos-

sess one or more environmental and/or social principles which can affect the purchasing

decision of the consumer. (Berry & McEachern 2005; Bezençon & Blili 2010; Ethical

Consumer 2018.) Demand for sustainability, however, did not originate from consumer

stakeholders alone.

The severity of climate change is a generally acknowledged fact and its consequences

are becoming increasingly dire in terms of human casualties and monetary damages. In

the field of supply chain management (SCM), the accelerating pace of climate change

and its disastrous consequences in form of increasingly devastating weather phenomena

have also been acknowledged. (Chen & Wang 2016.) As a manifestation of this realisa-

tion, low carbon supply chain management (LCSCM) is gaining momentum in both aca-

demic and industrial realms alongside GSCM and SSCM. Whereas GSCM is a very broad

concept, LCSCM adopts a more specific perspective. Aiming at the abatement of CO2,

CO2 equivalent or greenhouse gas (GHG) emissions in supply chains operations, concept

of LCSCM also incorporates carbon footprint accounting and monitoring. (Zhou et al.

2016; Das & Jharkharia 2018.)

Stakeholders, led by legislators, non-governmental organisations (NGO) and consum-

ers, are, in growing numbers acting to combat climate change with treaties and regulation

with an aim to reduce emissions (Meixell & Luoma 2015). One of the most prominent

examples of such a treaty is the Paris agreement striving to limit the global temperature

rise well below 2°C above pre-industrial levels and further pursue efforts to limit the rise

to 1.5°C (UNFCC 2018). The recent Special Report on Global Warming of 1.5°C by

Intergovernmental Panel on Climate Change (IPCC) verified the true graveness of the

current situation and the future of unprecedented climate disasters unless GHG emissions

are swiftly and considerably cut (IPCC 2018). Tightening regulation has forced compa-

nies to engage in GSCM and SSCM practices with growing fervour. Stakeholders are

using pressure as a means to impose regulation on companies, demanding for environ-

mental and social reforms in value-creating activities. (DiMaggio & Powell 1983; Lee et

al. 2014; Seles et al. 2016.)

In terms of stakeholder pressure, the most visible company in the supply chain expe-

riences the most pressure. This company is oftentimes located relatively close to the end

consumer in the downstream of the supply chain and possesses considerable negotiation

power over other companies, its suppliers, in the supply chain. (Chiu & Sharfman 2011;

Wolf 2014; Seles et al. 2016; Schmidt et al. 2017.) Nestlé is a prominent example of such

a company. Through their well-known and recognisable brands, these companies most

often experience the entirety of stakeholder pressure, even if the controversy was caused

by a supplier at the upstream of the supply chain—a phenomenon known as the chain

13

liability effect (Hartmann & Moeller 2014; Wilhelm et al. 2016). To understand the trans-

formation of stakeholder pressure into requirements for environmental and social reforms

in supply chains, we must first comprehend bullwhip effect.

Bullwhip effect refers to ineffective allocation of resources in a supply chain caused

by distorted demand data. In academic literature the concept of bullwhip effect has been

widely addressed by Lee et al. (1997a; 1997b). As each tier in a supply chain attempts to

respond rationally to demand higher than normal, managers in charge of different value-

creating activities along a supply chain tend to create a safety buffer for themselves by

ordering beyond the actual need. This practice sends an erroneous signal of increased

demand to the next-in-line, and demand information is further distorted by each tier in

the supply chain. When the demand eventually returns to, or sinks even below, previous

levels, stocks of products start to inevitably accumulate along the supply chain, tying up

working capital in the process. (Lee et al. 1997a; 1997b.) The legendary Beer Game is

also based on this phenomenon (Dizikes 2013).

The external, coercive pressure imposed on companies governing their supply chains

by stakeholders has been observed to trigger an extension of the traditional bullwhip ef-

fect (DiMaggio & Powell 1983; Lee et al. 2014; Seles et al. 2016). Analogously to de-

mand information moving through a supply chain exposed to the bullwhip effect, stake-

holder pressure also moves through a supply chain. Instead of the bullwhip effect, its

extensions, green and social bullwhip effect, influence stakeholder pressure in a supply

chain. In contrast to the bullwhip effect, these extensions have been examined to a lesser

extent in academic literature.

Green bullwhip effect refers to the process where the company governing the supply

chain transforms environmental pressures received from stakeholders into more stringent

environmental requirements and relays them to the preceding tier in the supply chain.

First-tier supplier assesses the requirement and like the company before it, seeks to build

a safety buffer by tightening the requirements for its own supplier. Environmental re-

quirements continue to become more stringent in terms of content or implementation

deadlines as they move towards the upstream companies. As a result, the first company

in the supply chain, manufacturer of raw materials or components, faces the most strin-

gent environmental requirements. (Lee et al. 2014; Seles et al. 2016.)

The existence of possible social bullwhip effect has been scarcely explored. Social

bullwhip effect, in reference to its green counterpart, would be triggered by stakeholder

pressure concerning social issues and would then be rendered into increasingly stringent

requirements along the supply chain. The aim of this thesis is to fill the research gap on

the distribution of sustainability within a manufacturing supply chain and explore the

concept of social bullwhip effect. Distribution of sustainability refers to the pattern sus-

tainability displays in a supply chain—whether sustainability distributes evenly, if it ac-

14

cumulates to a specific supply chain position, increases towards the upstream or distrib-

utes completely differently than the ways described before. By better understanding the

nature of environmental and social sustainability distribution, it would be possible to

make supply chains transparent to a greater extent and turn the attention of stakeholders

to the least sustainable parts of a supply chain. Discovering the possible effect the industry

of a company has on sustainability could also aid the stakeholders to better comprehend

the possible interdependence relationship between types of certain business activities and

sustainability, and thus point out industries more prone to sustainability misconduct.

1.2 Research questions & structure of the thesis

Distribution of sustainability in supply chain between supply chain positions is studied in

this research. Sustainability is assessed from two perspectives, environmental and social.

In addition, the interdependence between sustainability and industries of the sample com-

panies will be studied. For this research, quantitative environmental, social and corporate

governance (ESG) data available from sample companies is utilised and analysis of vari-

ance is applied to examine how environmental and social sustainability distribute along a

supply chain. Sample is collected from European large manufacturing, wholesale and re-

tail companies involved in manufacturing supply chains. All sample companies are part

of the STOXX® Europe 600 index. Sample companies are divided into three supply chain

positions: manufacturer 1 whose value-creating activities comprise extraction of raw ma-

terials and production of components; manufacturer 2 assembling end products; and ven-

dor, whose business activities constitute of wholesale and retail activities.

Research questions are as follows:

• How does environmental and social sustainability distribute in manufacturing

supply chains between supply chain positions?

• How does the industry of a company affect environmental and social

sustainability?

Using these research questions, this thesis also investigates the possible existence of

social bullwhip effect in addition to seeking additional evidence to the existence of the

green bullwhip effect.

This thesis consists of seven chapters. Chapters 2–4 serve as a literature review and

provide theoretical background on the researched phenomena, whereas Chapter 5 pre-

sents the hypotheses formulated based on the research questions above. Chapter 6 intro-

duces the scientific methodology, data used and methods of data analysis. Chapter 7 pre-

sents the results of the empirical research conducted and Chapter 8 connects the results

to the academic literature and previous research. Chapter 8 also discusses the theoretical

and practical implications of the results and suggests further research topics.

15

2 DEMAND FOR ENVIRONMENTAL AND SOCIAL

SUSTAINABILITY IN BUSINESS

2.1 Dawn of modern sustainability concept: triple bottom line

The concept of triple bottom line (TBL) was coined and later popularised by Elkington

in 1994 (Elkington 2018). Elkington’s vision was to create a sustainability framework

examining the impact of corporate value-creating activities across three dimensions—

economic, environmental and social. TBL was the manifestation of “people, planet,

profit” triangle, striving to treat economic, environmental and social measures as equally

important. Using TBL, environmental consideration and actualisation of social justice in

value-creating activities were intended to be monitored by using audits and reports, just

like economic performance. (Elkington 1999.)

Elkington has previously presented concepts highlighting the environmental aspect in

conducting business; environmental excellence in 1984 and green consumer in 1986, but

TBL was the first concept spearheaded by Elkington to incorporate the social element

alongside environmental and economic dimensions (Elkington 2004). Prior to this, logis-

tics and supply chain management literature had principally contemplated issues concern-

ing environment, actualisation of human rights and safety at workplace as well as max-

imising efficiency in production processes as separate, independent phenomena (Carter

& Jennings 2002; Carter & Rogers 2008). Savitz and Weber (2006) hailed sustainability

as the new fundamental principle of smart management. According to Wu and Pagell

(2011), TBL leads to sustainability in the long term and exposes decision makers of or-

ganisations implementing TBL to fewer strategic trade-offs between environmental, so-

cial and economic performance than decision makers representing organisations not hav-

ing adopted TBL in their value-creating activities.

Emergence of TBL has inspired a wide range of different sustainability reporting

measures, e.g. Global Reporting Initiative (GRI) in 1997, Dow Jones Sustainability Indi-

ces (DJSI) in 1999 and social return on investment—a methodology converting the envi-

ronmental and social value of an investment into monetary terms—which has been dis-

cussed in academic literature already in 2000 (Millar & Hall 2013; GRI 2018;

RobecoSAM 2018). In addition, various other environmental, social and corporate gov-

ernance (ESG) measures including the one used in this research, Thomson Reuters ESG

scoring, have their origins in TBL (Thomson Reuters 2018).

16

2.2 Criticism of triple bottom line

Like many concepts before, TBL has not been without criticism either. MacDonald and

Norman (2007) commented on the adoption of TBL by hundreds of organisations— web-

sites and documents containing enthusiastic announcements of TBL in use and endorse-

ments for the concept—stating that the implementation in most cases was done without

any critical scrutiny. Claiming the concept of TBL to have noteworthy shortcomings,

MacDonald and Norman (2007) view the use of an accounting paradigm to evaluate a

company and the ethical dimensions of the said company as a fundamentally unfit method

for the task—how can environmental or social performance be condensed into single bot-

tom line? The plethora of measures reported in various units cannot be treated in the same

manner financial information is treated in terms of commensurability. MacDonald and

Norman (2007) went on and compared financial bottom line to a so-called social bottom

line using the following example: how could the secretary answer to the question of the

managing director, has the social bottom line of the company increased or decreased from

last year. In the case of financial bottom line, this question could be answered. However,

with social bottom line in question, no unambiguous answer could be provided. (Norman

& MacDonald 2004; MacDonald & Norman 2007.)

Milne and Gray (2013) animadvert upon TBL for distorting the definition of what are

considered sufficient corporate actions to sustain the planet’s ecology. Milne and Gray

(2013) claim that TBL and GRI in fact bolster unsustainable business practices by pre-

senting those as an adequate standard. Mixing the incomplete TBL reporting with true

sustainability further exacerbates the situation as managers falsely believe that the com-

panies they represent conduct business in an environmentally, and ecologically, sustain-

able manner (Milne & Gray 2013). Bansal and Song (2017) argue that the recent integra-

tion of economy, society and environment by scholars has shifted the paradigm from how

to sustain systems to how companies can sustain systems, thereby elevating companies

as the ultimate stakeholder. Consequently, economic interests of a company can become

a starting point in research and sustaining these interests a goal in practice as trade-offs

are made between the three domains, economy, society and environment. Managers

would implement social and environmental sustainability practices only if such practices

would be aligned with the strategic interests of the company or have profit expectations

(Bansal & Song 2017). As some of the planet’s natural resources are depleting at an

alarming rate, Pagell and Shevchenko (2014) urge future SCM research to examine envi-

ronmental and social performance of supply chains at the very least as equally important

or preferably more crucial than the ability to generate profit.

Montabon et al. (2016), in turn, questioned the prevailing TBL doctrine. The ultimate

driver for implementing environmentally and socially sustainable practices in TBL is the

economic gain. Instead of this mindset, the question “how can a supply chain become

17

sustainable” must be asked—harm reduction does not lead to true sustainability. As an

alternative to, or as an improvement of TBL, Montabon et al. (2016) propose the concept

of ecologically dominant logic. Whereas the traditional logic currently in place in the

corporate world emphasises the economic aspect of business, ecologically dominant logic

would nest social and economic issues inside environmental issues and economic issues

within social issues. This change of perspective first satisfies environmental needs fol-

lowed the fulfilment of social needs and only then turns to fulfilling customer demands

in contrast to the short-term profit-seeking practice with an aim only to mitigate negative

long-term environmental and social outcomes. As environment is the “great enabler”,

providing societies with a living environment and a chance to conduct business in the first

place, environment is incontestably the ultimate constraint in the equation for generating

profit. (Montabon et al. 2016.) Comparison of different sustainability concepts is pro-

vided in Figure 1.

Note Used abbreviations: econ. = economic; envr. = environmental;

soc. = social

Figure 1 Comparison of TBL how it was intended by Elkington, how TBL is often

implemented in practice and the ecologically dominant logic leading to

true sustainability (adapted from Elkington 1999; Adams 2006; Adams et

al. 2009; Montabon 2016; Mulia et al. 2016)

Ecologically dominant logic is not the first concept to place environment ahead of

society and economic gain, yet it is one of the first to do so in the field of SCM. As early

as 1991, Henderson introduced the layer cake model where Mother nature forms the foun-

dation for upper layers which are the society—the love economy, including e.g. volun-

teering work, parenting, community structures—and public and private sector, the gross

national product monetised half of the cake. Above all this rests the market economy with

its cash transactions. The layer cake model is displayed in Figure 2. (Henderson 1991.)

18

Figure 2 Layer cake model distinguishing the interdependence between environ-

mental, social and economic dimension (adapted from Henderson 1991;

Cato 2008)

The impact of sustainability reporting on truly changing corporate behaviour has been

questioned. Some scholars and organisations, e.g. Christian Aid (2004), Gray (2006),

Murray et al. (2017), claim that corporate responsibility reporting acts as a mere

smokescreen and the status quo, unsustainable operations, prevails behind the façade of

reporting. In June 2018, “the father” of TBL himself issued a recall on the concept.

Elkington purports that TBL has been mostly adopted as an accounting tool, not as a

holistic way of conducting business. According to Elkington, TBL, once a revolutionary

idea, has been diluted by the excessive amount of sustainability reporting. This view is

shared by Tim Mohin, GRI’s Chief Executive. Both individuals demand for harmonisa-

tion among various reporting standards, Mohin, in an interview given to Ethical Corpo-

ration, calling for more effective data applications instead of traditional company-pro-

duced marketing reports, which attract little mainstream investment community attention

(Slavin 2018). Mohin insists that data should be more concise, always up-to-date and data

should be exploited to forecast upcoming trends and events. Both Elkington and Mohin

agree that TBL-based ESG data is needed more than ever before, but the data must still

be in an instantly accessible, clear and applicable form for different purposes. (Elkington

2018; Slavin 2018.)

19

2.3 Notions on sustainability in the academic realm

Due to human-induced climate change finally becoming a generally recognised fact, at

the latest after the signing of the Paris agreement, heeding the environment is of ever-

increasing importance to conducting business. Environmental considerations have al-

ready been incorporated into the daily operations of many companies. (UNFCC 2018.) In

the field of SCM, doctrines aiming to establish green supply chains are gaining foothold

among management practices as means to comply with constantly tightening environ-

mental legislation and to create competitive advantage (Rajeev et al. 2017; Taborga et al.

2018). Green supply chains strive to integrate the environmental aspect into all the oper-

ations conducted in the chain from product design to end-of-life management of the prod-

uct (Srivastava 2007).

Competitive advantage can also appear as product or service differentiation, and thus

is not only restricted to process-based cost reductions and efficiency improvements (Laari

et al. 2017). Climate change is to be blamed for both increased frequency and magnitude

of extreme weather phenomena in the recent years and this observation has had its reper-

cussions on SCM practices as well (Mal et al. 2017; Herring et al. 2018). IPCC’s special

report on the devastating effects of global temperature average increasing by more than

1.5°C above pre-industrial levels has given further impetus to conduct business in a more

environmentally friendly manner, and many legislating bodies have expressed their con-

cern for the situation globally and spoken for severely tightening environmental regula-

tion in many sectors of society (IPCC 2018; Willuhn 2018).

However, Van der Leeuw et al. (2012, 118) state that academia is poorly positioned in

addressing sustainability issues and “suffers from anachronistic pedagogy, inertia, and

disciplinary insularity and isolation”. Bursztyn and Drummond (2014) assert that non-

academic research institutions are more flexible than universities in responding to prob-

lem-oriented demands. Interdisciplinary research and training programmes in the field of

sustainability are still in the nascent stage in universities in comparison to the situation in

non-academic research institutions. This hinders the realisation of synergies between dif-

ferent faculties through multidisciplinary research teams and exchange of knowledge in

universities. Universities are being pushed to differentiate their study modules and spe-

cialise at the cost of encompassing perspective. Non-academic research institutions ben-

efit from a more pragmatic, problem-oriented approach in research in contrast to the

somewhat fixed department and faculty structure of universities. More adaptive and re-

sponsive multidisciplinary task forces may be deployed and shuffled into new teams in a

much more agile fashion than research teams of the academic world. (Bursztyn & Drum-

mond 2014.)

Another factor impeding the attempts of academia to address sustainability issues is

the use of terminology. Sustainability and responsibility are oftentimes used as synonyms

20

in an inconsistent and ambiguous fashion. These two concepts have displayed conver-

gence only during the last two decades, albeit having evolved from different paradigms.

Responsibility originally focused on social issues and sustainability examined environ-

mental concerns. (Bansal & Song 2017.) Bansal and Song (2017) argue that the semantic

blurring between sustainability and responsibility has resulted in the stagnation of both

fields of research, omitting vast, potential areas of study which could generate further

knowledge of the relationship between business and society. Outside the academic realm,

notable actors have also fostered the ambiguity of terminology, one prominent example

being United Nations Global Compact defining their mission—“by committing to sus-

tainability, business can take shared responsibility for achieving a better world” (United

Nations Global Compact 2018).

In parallel to Bansal and Song (2017), Van der Leeuw et al. (2012) assert that academia

is circumventing urgent and severe issues e.g. climate change, loss of biodiversity and

poverty as the discussion is ridden with a plethora of interpretations of sustainability.

These interpretations are coupled with own methodological choices, goals and frame-

works of each interpretation causing fragmentation of the discourse, resulting in the use

of rhetoric in a mismatch with real-world sustainability transitions. (Van der Leeuw et al.

2012.) While out of touch with reality, academia ought to seek and establish partnerships

with actors from industry, NGO field and other stakeholders of the society. This rap-

prochement would initiate a transition towards a sustainability solution orientation as pro-

posed by Van der Leeuw et al. (2012) and Yarime et al. (2012), drawing parallels to the

proposals made by Bursztyn and Drummond (2014) to develop interdisciplinary research

and training programmes in the field of sustainability and deepen the interaction with

non-academic research institutions.

2.4 Under pressure—a stakeholder perspective on sustainability

DiMaggio and Powell (1983) introduced three mechanisms which act as drivers of insti-

tutional isomorphism. Institutional isomorphism can be defined, in a straightforward

manner, as a process where organisations operating in the same organisational field start

to eventually resemble one another as rational actors representing those organisations

strive for improvements. This homogenisation process is triggered by three mechanisms:

coercive, mimetic and normative pressure. Mimetic pressure results in organisations

mimicking each other’s responses to uncertainty, whereas normative pressure drives

members of an occupation to unite their forces in a process called professionalisation.

Coercive isomorphism, however, is manifested in an organisation when other organisa-

tions, also known as stakeholders in this context, exert formal or informal pressures on

the examined organisation. (DiMaggio & Powell 1983.) Such pressure can be perceived

21

in a positive or negative fashion—”as force, as persuasion, or as invitations to join in

collusion” (DiMaggio & Powell 1983, 150). Organisations, which depend on stakeholder

organisations e.g. manufacturers dependent on their customers, are exposed to certain

requirements. In terms of sustainability, manufacturers have a strong imperative to reduce

emissions of their value-creating activities as their customers in the downstream of the

supply chain, on their behalf, are being exposed to pressure as a result of the emission

control policies introduced by their government or by some other legislative body. Emis-

sion performance of suppliers might also play a key role due to the legislative pressure

when the customer company in the downstream shortlists potential manufacturers. (Hu et

al. 2015; Jabbour et al. 2015; Kuo et al. 2015.) The surrounding society may also impose

cultural expectations on the company, for example, local community might require a for-

eign company to operate according to ethical business practices customary to the country

in question. (DiMaggio & Powell 1983.)

One of the most prominent stakeholder groups are consumers (Seles et al. 2016). Pos-

sessing purchasing power, being the end user of the proliferation of manufactured goods

produced and the ultimate mainstay of the whole capitalist system, consumers with their

decisions dictate the survival and prosperity of companies in manufacturing supply

chains. Not simply being limited to the decision to buy or not, consumers can also rally

others behind the cause of boycotting certain brands. One of the growing consumer move-

ments, and subsequently also one growing market, is ethical consumerism. (Berry &

McEachern 2005; Bezençon & Blili 2010; Ethical Consumer 2018.) Ethical consumerism

is defined as “the intentional purchase of products considered to be made with minimal

harm to humans, animals and the natural environment” by Burke et al. (2014, 2237) who

adapted their definition from Auger et al. (2003), Bray et al. (2011) and Papaoikonomou

et al. (2012).

Ethical consumerism has displayed growing importance financially and in terms of

consumer attitudes and concerns during the last decade. Consumers are increasingly con-

cerned about environmental and social facets of production processes, and the number of

consumers willing to pay a premium for products produced by socially responsible com-

panies is on the rise. In United Kingdom, ethical spending in 2005–2011 increased by one

third to a total market value of GBP 47.2 billion. By 2017, the total market value had

increased by over three quarters from the figure of 2011 to GBP 83.3 billion, a growth

driven primarily by increased environmental concern. Additionally, during 2017 almost

the half of (49 %) of consumers under 24 years of age avoided a product or service based

on its negative environmental impact according to a report by Ethical Consumer. (Bonini

& Oppenheim 2008; Ethical Consumer 2012; 2018; Nielsen 2013; Burke et al. 2014.)

Consumers engaging in conscious consumption, not merely purchasing ethical products

but also reducing consumption overall, are also more prone to political engagement, act-

ing as active citizens and making individualised decisions opposed to collective ones.

22

Such consumers have the possibility to exert further influence on manufacturing supply

chains through fostering social change. (Willis & Schor 2012.) Oftentimes, ethical con-

sumerism is viewed exclusively as a Western phenomenon displayed in post-industrial

societies, but signs of similar trends and preferences have been observed to emerge also

in developing economies (Balasubramanian & Soman 2018). For instance, China has

based its economic planning on the concept of circular economy in three of its Five-Year

Plans 2006–2020, signalling of a salient change in mindset towards consideration for the

environment (Zhang et al. 2008; Central Compilation & Translation Press 2016; Murray

et al. 2017).

Alongside environmental aspect gaining momentum in conducting business, social

sustainability is also becoming an integral part of modern business practices. Failing to

comply with current standards of social sustainability imposed on the supply chain leads

to widely reported media controversies, which spread rapidly in the era of easily accessi-

ble social media. For example, technology giant Apple has often been accused of, in some

cases inhumane, working conditions and inadequate safety measures of its suppliers,

which led e.g. to the explosion at the site of Apple’s main supplier Foxconn in China 2011

killing four and injuring 18 workers and prompting a boycott campaign against Apple in

2012 (Duhigg & Barboza 2012; Harris 2012). World’s largest food and beverage com-

pany Nestlé, in turn, has faced heavy criticism due to its unsustainable and unethical busi-

ness practices (Tennant 2015; White 2017; Fullerton 2018). Component suppliers of Sam-

sung in Malaysia have been, in a similar vein, exposed for e.g. confiscating the passports

of their labour force, thus forcing them to live in constant fear of deportation. Same sup-

pliers have also been paying considerably smaller wages than initially promised, render-

ing some of the workers effectively modern slaves working to pay back just the loan they

took to settle the initial the recruitment fee. (Pattison 2018.)

Other repercussions from violating social sustainability standards than media backlash

can be e.g. having to pay considerable compensations for damages and the loss of inves-

tors and/or customers (Yawar & Seuring 2017). Prominent cases regarding indemnity

include California State Court ordering agrochemical and agricultural biotechnology cor-

poration Monsanto to pay a former groundskeeper USD 289 million as the company’s

weedkiller product caused the groundskeeper to develop cancer. The sum was later low-

ered to USD 78.5 million. (Levin & Greenfield 2018; Wamsley 2018.) In May 2019,

Monsanto has been obliged to pay more than USD 2 billion in damages to a California

couple due to cancer discovered in both wife and husband. The cancer was caused or

contributed by herbicide glyphosate used by Monsanto in some of its products. (Blank-

stein & Kaplan 2019.)

In addition to direct demand for environmental and social sustainability, corporate so-

cial responsibility (CSR) practices have also been studied to have a considerable influence

23

on consumer perceptions of brand equity (Kang & Namkung 2018). United Nations In-

dustrial Development Organization defines CSR as “a management concept whereby

companies integrate social and environmental concerns in their business operations and

interactions with stakeholders”. The term encompasses economic, social and environ-

mental performance—social performance can be measured in e.g. the state of working

conditions, realisation of human rights at the workplace and the quality of governance

policy. (UNIDO 2018.)

Consumers are not the sole stakeholder group pressurising companies to conduct busi-

ness in an environmentally and socially sustainable manner. Other stakeholder groups

such as legislators and NGOs face a troublesome task of monitoring the realisation of

sustainability from the start to the end of the process in growingly complex manufacturing

supply chains (Cannella et al. 2018). Through their own direct and indirect monitoring

and pressurising activities, the stakeholders—competitors, communities, NGOs, govern-

ments and customers—initiate the implementation of green supply chain management

(GSCM) and sustainable supply chain management (SSCM) practices by exerting influ-

ence on the most visible company in the supply chain with considerable negotiation power

over its suppliers—a company governing the supply chain (Seles et al. 2016; Schmidt et

al. 2017). Comprehensive definitions for GSCM and SSCM will be provided in Chapters

3.1 and 3.2, but for the sake of clarity, a short definition is provided already here. GSCM

aims at “greening” supply chains and SSCM incorporates social reforms alongside with

green initiatives in supply chains (Srivastava 2007; Seuring & Müller 2008).

Regarding SSCM, Meixell and Luoma (2015) discovered that stakeholder pressure

may result in three different outcomes for a company, and for a supply chain at large.

Firstly, stakeholder pressure may raise awareness of sustainability within a company.

Pressure may also lead to the company setting sustainability goals and, ultimately, result

in the implementation of SSCM practices. Secondly, stakeholder type also affects where

the pressure is felt—media pressure most often affects purchasing decisions and share-

holders, in turn, influence logistics decisions. Finally, stakeholder type also effects the

dimension of sustainability targeted: social sustainability is predominantly enforced by

employees and NGOs, whereas environmental sustainability is affected by external stake-

holders e.g. governmental bodies and end consumers. (Meixell & Luoma 2015.)

Wolf (2014) dissected the relationship between SSCM, stakeholder pressure and cor-

porate sustainability performance, being among the first to assert that supply chains, and

thus companies, could benefit from implementing SSCM beyond reduction of stakeholder

pressure. Wolf (2014) discovered that SSCM can grant companies access to key re-

sources, enhance their reputation as a “good citizen” and develop unique resources and

capabilities, challenging the view that external stakeholder pressure is the sole driver for

SSCM. Stakeholders were observed to engage in two strategies regarding key resources,

withhold and usage strategies. In the example of Nestlé and its palm oil supplier Sinar

24

Mas, Nestlé first applied the withhold strategy, but later switched to usage strategy.

Greenpeace exerted pressure over Nestlé to end the supply of unsustainably extracted

palm oil by Sinar Mas, where Greenpeace succeeded. Nestlé later re-established the sup-

ply relationship with Sinar Mas with the condition that the said supplier upgrades its op-

erations to meet the standards of sustainable palm oil production certificate issuer. (Wolf

2014.)

Stakeholders have been proven to punish the company governing the supply chain

most severely even for the non-compliance of its suppliers. Stakeholders, however, have

trouble reaching any other supply chain positions in the chain beyond the companies most

visible to the public at the downstream of the supply chain. As supply chains oftentimes

possess little transparency and are complex in design, the sustainability of operations

along the line is hard to assess (Cannella et al. 2018). In other words, global brands may

receive negative publicity due to lower-tier suppliers not adhering to sustainability stand-

ards. This phenomenon is known as the chain liability effect. Concluded by Hartmann

and Moeller (2014), in the case of an environmental degradation incident, consumers

might comprehend how arduous and complex of a task enforcing sustainability through-

out the entire supply chain imposed on the company governing the supply is, but none-

theless still resort to blame the governing company for the dereliction of standards com-

mitted by its suppliers for the sake of convenience. (Hartmann & Moeller 2014; Wilhelm

et al. 2016; Villena & Gioia 2018.)

25

3 ENVIRONMENTAL AND SOCIAL SUSTAINABILITY

MANAGEMENT & MEASUREMENT

3.1 Green Supply Chain Management

TBL has inspired two often intertwining concepts, green supply chain management

(GSCM) and sustainable supply chain management (SSCM). Payman and Searcy (2013)

studied the differences between these two definitions, which are frequently used inter-

changeably even by scholars. In general, GSCM has intrinsically emphasised the envi-

ronmental dimension of SCM operations, whereas SSCM takes a more holistic approach

including all three elements of TBL sustainability, “people, planet, profit”. Srivastava

(2007) has been one of the pioneers in the field of GSCM conducting a literature review

of various GSCM definitions. His interpretation of GSCM incorporates a life cycle ap-

proach into the definition as he describes GSCM as “integrating environmental thinking

into supply-chain management, including product design, material sourcing and selection,

manufacturing processes, delivery of the final product to the consumers as well as end-

of-life management of the product after its useful life” (Srivastava 2007, 54).

Zhu et al. (2012) divide GSCM practices into internal and external ones—previous

encompass practices implemented in-house such as eco-design and environmental man-

agement, whereas latter includes transactions with suppliers and customers. Concrete ex-

amples of internal GSCM practices are pollution prevention programmes in internal pro-

cesses, special training for workers on environmental issues, and collection and sale of

scrap and used materials. External GSCM practices include e.g. requiring suppliers to

have an ISO 14001 (environmental management system) certification and co-operation

with customers for green packaging and for reverse logistics agreements. (Zhu et al.

2012.) Schmidt et al. (2017) base their categorisation of GSCM practices on several aca-

demic publications and divide practices into green design, green internal management,

green logistics, green purchasing and green manufacturing.

One of the latest trends affecting the field of GSCM is the transition towards circular

economy, one prominent example of this being China. Circular economy is defined as

“an economic model wherein planning, resourcing, procurement, production and repro-

cessing are designed and managed, as both process and output, to maximise ecosystem

functioning and human well-being" (Murray et al. 2017, 377). As opposed to the construct

of linear economy, where natural resources are converted into waste by means of produc-

tion, circular economy seeks to manage the flux of resources in cycles. Aiming for no net

effect on the environment, circular economy strives for restoring damage inflicted on the

environment in resource extraction phase and minimising waste generation throughout

the life cycle of a product based on the principle of three Rs: reduce, reuse and recycle.

26

When resources stay in the cycle for longer, waste output is delayed, and both rate of

replacement and need for resources decrease. (Murray et al. 2017.) Much like certain

early GSCM practices before they matured, the concept of circular economy has been

recognised as a means for achieving competitive advantage (Genovese et al. 2017; Ellen

MacArthur Foundation 2019). Genovese et al. (2017) identify clear advantages from in-

tegrating circular economy principles in GSCM practices, especially production-related,

from an environmental point of view.

Another concept analogous to GSCM is low carbon supply chain management

(LCSCM). The number of journal articles addressing carbon emission issues in supply

chain management has increased sharply from 2010 onwards, albeit research on carbon

emissions issues in SCM is still a fledgling field of research. Das and Jharkharia (2018),

in their comprehensive literature review on LCSCM, suggest the Kyoto Protocol, which

placed legislative pressure on organisations for abating emissions in 2005, as a possible

reason for the emerging LCSCM trend. The definition of LCSCM according to Das and

Jharkharia (2018, 399) is “a strategy that integrates CO2 or CO2 equivalent or GHG emis-

sions either as a constraint or as an objective in supply chain design and planning”.

In comparison to green or sustainable supply chain management, LCSCM represents

a more specific approach to involve environmental concerns in supply chain activities

from a pollution point of view as the concept revolves around carbon emission reduction.

Such reduction can be achieved by e.g. selecting suppliers, managing transportations and

designing networks with emission abatement as a driver. Furthermore, LCSCM also high-

lights the need for carbon footprint accounting and conceptualisation in SCM and

acknowledges the need for trade-offs between economic and environmental objectives

across different supply chain functions. (Zhou et al. 2016; Das & Jharkharia 2018.)

3.2 Sustainable Supply Chain Management

During the last decades, SSCM has transitioned from the marginal into the research main-

stream. SSCM definitions have comprehensively been mapped by Seuring and Müller

(2008) and they propose two different strategies—one focusing on suppliers in terms of

risk and performance while the other one takes a product-based stance. As stated by

Seuring and Müller (2008, 1700), the definition of SSCM is “the management of material,

information and capital flows as well as cooperation among companies along the supply

chain while taking goals from all three dimensions of sustainable development, i.e., eco-

nomic, environmental and social, into account which are derived from customer and

stakeholder requirements”. Considering this definition, SSCM can be regarded as an ex-

tension of GSCM introducing the social aspect, and thus sharing the threefold division

framework with TBL (Pagell & Shevchenko 2014).

27

Nonetheless, comprehensive mapping effort has not succeeded in ending the treatment

of SSCM as s separate entity of SCM. Pagell and Shevchenko (2014) claim that five

salient issues prevent the discovery of new practices and procedures to create truly sus-

tainable supply chains. Preponderance of studies in both fields, GSCM and SSCM, have

been dictated by the question “does it pay to be green” which places the focus on eco-

nomic performance of a company, neglecting the development of harm elimination. Re-

garding stakeholder prioritisation, managers and shareholders are predominantly viewed

as the most important stakeholders in a supply chain, effectively elevating the fulfilment

of monetary goals above all else. (Hart & Ahuja 1996; Ambec & Lanoie 2008; Carter &

Rogers 2008.)

The development of SSCM research has also been hindered by concentration on fa-

miliar practices. Explorative SSCM practice studies are few in number as the majority of

studies are limited to merely examining how existing practices can transform unsustain-

able supply chains to less unsustainable, thus setting the standard as damage mitigation

instead of elimination. Pagell and Shevchenko (2014) also name unfit empirical tools and

ill-suited measures as impediments for reaching truly sustainable supply chains. Aca-

demia has lagged behind the development of industry and empirical tools are currently

formulated to answer “what” questions, rather than “how” questions, and have a historical

emphasis. Such tools thus have a built-in propensity to neglect radically innovating sup-

ply chains. Measures serving as indicators of supply chain impacts are largely based on

secondary data as managerial perceptions on environmental and social issues are often

subjective. Measures utilising secondary data generally fail to capture impacts of entire

supply chains. (Pagell & Shevchenko 2014.)

The social dimension of supply chain management has been overshadowed by the pro-

liferation of GSCM practices (Yawar & Seuring 2017). Klassen and Vereecke (2012, 103)

determine social issues in supply chains as “product or process related aspects of opera-

tions that affect human safety, welfare and community development”. Yawar and Seuring

(2017) use the term responsible supply chain actions when referring to practices solving

social issues in supply chains. They divide such practices to communication, compliance

and supplier development strategies. The objective of communication strategies is to e.g.

address stakeholder concerns and commit customers by presenting sustainable operations

in communication. Typical practices include sustainability reporting and product label-

ling which conveys product characteristics in a transparent fashion. Instruments of com-

pliance strategies include codes of conducts, standards, and auditing and monitoring

measures. Two previous ones aim to solve social issues occurring in supply chains,

whereas the latter two, auditing and monitoring, track the implementation of practices

required to meet standards, and measure the impact of sustainability practice adaptation

on supplier performance. The most popular practice for resolving social issues is the im-

28

plementation of codes of conduct and standards (Van Tulder et al. 2009). Supplier devel-

opment strategies in practice comprise collaborations, training, investments into assets,

and financial and technical support (Krause et al. 2007). As companies governing supply

chains are oftentimes held accountable for social sustainability of the whole chain, the

social performance of suppliers is of importance to both internal and external stakeholders

(Yawar & Seuring 2017).

One concrete example of social sustainability practices, and more specifically of codes

of conduct and standards, is SA8000 social certification. SA8000 is measuring social per-

formance through eight criteria, which include abstaining from child labour and enforcing

freedom of association. The implementation of SA8000 along the supply chain is audited

and monitored by regular revisions. (Klassen & Vereecke 2012; Social Accountability

International 2018.) Other types of examples are joint social development projects in col-

laboration with stakeholders from local communities, for instance, building a school and

funding research and education aimed at improving women’s healthcare (Klassen & Ve-

reecke 2012).

3.3 From financial performance measurement to sustainability

performance measurement

When it comes to monitoring economic sustainability, various metrics and measures exist

for assessing different aspects of economic performance of a company. Key performance

indicators (KPI) and ratios measuring profitability, liquidity, solvency, efficiency of asset

use and market value of a company appear numerous and diverse. (Investopedia 2019.)

As the primary objective of a company is to generate profit, these measures have tradi-

tionally received the most attention in business management (Rajnoha et al. 2016). In

numerical sense and in terms of maturity, ratios measuring sustainability have been lag-

ging behind financial ratios in development (Fowler & Hope 2007). Also, the obscurity

and lack of distinction among concepts and the subjective nature of sustainability assess-

ment—which level of performance is perceived as good or acceptable—have hindered

the development of instruments for measuring sustainability in supply chains (Pagell &

Shevchenko 2014; Bansal & Song 2017; Yawar & Seuring 2017).

One plausible reason explaining the gap between the measure types available, along-

side focus on mere financial performance in the past, is the very nature of environmental

and social sustainability performance. Performance in these two fields is hard to detect or

express upon implementation of the practice, as the effects can often be recognised only

after a delay. The preponderance of research has focused on how does improving the

environmental and social dimensions of operations impact financial performance. (Pagell

& Shevchenko 2014; Friede et al. 2015; Laari et al. 2016; Lee et al. 2016.) Another factor

29

contributing to the enhanced emphasis on environmental and social sustainability meas-

uring is stakeholder pressure as last two decades have witnessed a transformation from

focusing on shareholder values to addressing the concerns of a wider stakeholder group

(Rajnoha et al. 2016).

Demand for diverse sustainability measures and indices is stronger than ever before as

e.g. increasingly many consumers want to make ethical choices and companies are re-

quired to conduct business in an ethical and sustainable manner by many stakeholder

groups (Hancock 2017; Ethical Consumer 2018; Russell 2018). Pressure to comply with

demands comes from legislative stakeholders, NGOs and consumers alike. In recent

years, the development of ratios measuring environmental and social sustainability per-

formance has been accelerating and the general attitude has been shifting from monitoring

primarily financial measures to strategic performance measurement involving all three

components of TBL. (Speziale & Klovienė 2014; Izadikhah & Farzipoor Saen 2016;

Rajnoha et al. 2016.) Performance measurement systems consist of a set of both financial

and non-financial measures which collect, process and analyse quantified data and ulti-

mately produce information to support the top brass of a company in decision-making

(Rajnoha et al. 2016). Such systems expand the scope beyond the realm of financial per-

formance measurement by involving non-financial indicators.

Strategic performance measurement systems (SPMS) are a derivative of performance

measurement systems, adding different perspectives to the examination of performance

of a company. When these perspectives—financial concerns, customer demands, internal

processes and long-term innovation—are combined, managers are presented with means

to translate company strategy into effective and sound performance measures, KPIs.

SPMSs possess the potential to recognise causal relationships between the operations and

strategy of a company with an aim to create a framework, where to formulate and imple-

ment strategies. (Chenhall 2005.) SPMSs can also be viewed as a strategy implementation

tool as through the KPIs, SPMSs contribute to the achievement of strategic goals through

a set of mechanisms. These mechanisms comprise enhanced understanding of links be-

tween different policy priorities, sound communication between objectives and activities

and lastly, allocation of resources and tasks in an efficient manner. (Dossi & Patelli 2010;

Rajnoha et al. 2016.) A typical example of a SPMS is the Balanced Scorecard (BSC), a

system of balanced objectives and indicators developed by Kaplan and Norton (1993).

BSC is defined by Figge et al. (2002, 279) as “a tool to identify the 15–25 strategically

most relevant aspects and to link them causally and hierarchically towards the long-term

success measured by the financial perspective”. BSC methodology is largely based on

stakeholder theory, presenting cause-effect relationships between operational and non-

business activities and long-term corporate strategy. Identifying these links, according to

Figge et al. (2002), leads to the prioritisation of activities based on their strategic im-

portance. Transformation from shareholder values to addressing concerns of a wider

30

stakeholder audience, through the adaption of sustainable-oriented BSCs, has resulted in

stakeholders examining the impact of value-creating activities on environment and soci-

ety more rigorously than previously. (Rajnoha et al. 2016.)

Searcy (2012) mapped the evolution of corporate sustainability performance measure-

ment systems (CSPMS), their implementation and use exhaustively in his review study.

In comparison to other performance measurement systems, CSPMSs are characterised by

the need to measure the ability of a system to adapt to change over an extended period of

time (Milman & Short 2008). A longer time span is required as the impacts of environ-

mental and social practices surface gradually as opposed to practices aiming to improve

financial bottom line resulting in sudden yields (Laari et al. 2016; Lee et al. 2016). An-

other difference to performance measures is the intrinsic focus of a CSPMS on environ-

mental and social dimensions of operations (Searcy 2012). CSPMS is defined by Searcy

(2012, 240) as “a system of indicators that provides a corporation with information

needed to help in the short and long-term management, controlling, planning, and perfor-

mance of the economic, environmental, and social activities undertaken by the corpora-

tion”—a system implementing TBL.

One of the CSPMS was developed as a direct upgrade of the BSC, to advance the

measurement of environmental and social impact of corporate operations. Figge et al.

(2002) introduced the Sustainability Balanced Scorecard to overcome the shortcomings

of the original BSC, which was ill-suited to comprehensively measure sustainability. The

process of developing a Sustainability BSC is threefold and includes the integration of

environmental and social management into business management, ensuring that the cre-

ated scorecard is business unit specific and unique in design, meets the specific charac-

teristics and requirements of the strategy and complies with the environmental and social

aspects of the business. Finally, environmental and social aspects of a business, which are

strategically relevant, are to be integrated. (Figge et al. 2002.)

3.4 Means of measuring sustainability

TBL has been used not only as a business management concept, but also as a tool to

measure sustainability, alongside Sustainability BSC. Slaper and Hall (2011), however,

have pointed out that no uniform standard on how to calculate TBL is in place nor is there

a universal agreement on the measures comprising the three categories of TBL. Sloan

(2010) identifies sets of management tools to assist companies in making sustainable de-

cisions and methods for reporting sustainability. These tools contain e.g. life cycle assess-

ment used to evaluate the impact of a product on the environment from design to disposal,

global efficiency ratio, environmentally conscious manufacturing programmes and the

31

previously introduced Sustainability BSC (Sloan 2010). Global efficiency ratio, devel-

oped by Barbiroli and Raggi in 2003, is a numeric index determining the impact of envi-

ronmental innovations on a specific process (Barbiroli & Raggi 2003). Sarkis (1999), in

turn, has innovated conscious manufacturing programmes where in the first phase of the

programme, factors affecting the selection of a manufacturing alternative are given rela-

tive weights through an analytical network process. In the second phase, data envelop-

ment analysis ranks the manufacturing alternatives (Sarkis 1999).

Measures used to analyse, and report sustainability are most often based on TBL con-

cept (Sloan 2010). GRI provides standards for economic, environmental and social per-

formance reporting. Such standards instruct how to collect, analyse and report sustaina-

bility information in a standardised form. (GRI 2018.) Another initiative focused on sus-

tainability is the Global Environmental Management Initiative (GEMI). Unlike GRI,

GEMI does not concentrate on developing and disseminating standards, but rather pro-

vides tools and consultancy for organisations to foster environmental sustainability and

health and safety at workplace, thus striving for reduced burden on the planet and safer

working environments. (Sloan 2010; GEMI 2019.)

Sustainability indices and measures generating numerical values are attempting to pro-

vide more objective data on sustainability than standard-based self-reporting initiatives.

Roberts Enterprise Development Fund developed social return on investment in 2000 as

a response to the growing pressure exerted on non-profit social enterprises to exhibit the

social value created by the enterprises in monetary terms (Low 2006). Social return on

investment results from dividing the net present value of benefits with the net present

value of investments (Millar & Hall 2013). Prominent indices incorporating all elements

of the “people, planet, profit” triangle include e.g. DJSI, Morgan Stanley Capital Interna-

tional (MSCI) ESG Ratings and Thomson Reuters ESG Scores. These indices take certain

measures, focusing on environmental, social and corporate governance performance, and

use these measures to calculate relative scores for individual companies, industries and

regions to render sustainability benchmarking, based on relatively objective data gener-

ated by a standardised process, possible. (RobecoSAM 2018; Thomson Reuters 2018;

MSCI 2019.)

Nine different indices with a specific geographical focus, e.g. DJSI Europe, DJSI Asia

Pacific and DJSI Korea, comprise the DJSI family. Dow Jones index families themselves

are six in total with each having a different emphasis. S&P Fossil Fuel Free index family

for instance tracks the performance of companies not in the possession of fossil fuel re-

serves and places additional weight on carbon emissions in performance evaluation.

Through the annual Corporate Sustainability Assessment, companies across 60 industries

are compared based on a questionnaire consisting of 80–100 cross-industry and industry-

specific questions. These results are then processed, and companies receive a score on a

32

range 0–100, where 100 is the best score, and a percentile ranking on 20 financially rele-

vant sustainability criteria, as a result. (RobecoSAM 2018; 2019.)

MSCI ESG Ratings and Thomson Reuters ESG Scores are more similar in design in

contrast to the self-evaluation methodology approach used by to DJSI. Analysts at MSCI

gather macro datasets generated by academical and governmental actors and NGOs, for

example, datasets of Transparency International and World Bank. Company disclosures,

e.g. sustainability reports, and the media are also among utilised data sources. Data is in

the next phase processed through the lens of 37 key issues selected annually for each

industry, and ultimately an ESG Letter Rating is issued for individual companies to be

used for benchmarking purposes. (MSCI 2019.) In the case of Thomson Reuters, ESG

Score is calculated in a very similar fashion to the rating of specific sustainability

measures used by MSCI, which are refined into comparable scores for over 7,000 com-

panies. Thomson Reuters ESG methodology is comprehensively described in Chapter 6.2

(Thomson Reuters 2018.)

33

4 BULLWHIP EFFECT AND ITS EXTENSIONS

4.1 Bullwhip effect encountered, recognised & popularised

The position of a company in the supply chain has been asserted to have a considerable

effect on stakeholder pressure and salience experienced by the company. Companies are

exposed to varying degrees of pressure in the supply chain based on the position of the

company. The inclination of stakeholders to apply pressure grows when the targeted com-

pany is visible to the public. (Siegel 2009; Wynstra et al. 2010; Lo 2013; Schmidt et al.

2017.) In this thesis, the definition of supply chain position (SCP) by Schmidt et al.

(2017), who derived their definition from Wynstra et al. (2010) and Lo (2013), is used

when referring to the business units and/or companies engaged in different value-creation

activities in the supply chain. Schmidt et al. (2017, 7) define SCP as the “the structural

position of a firm’s value creation activities within the overarching supply chain”,

Bullwhip effect in the field of SCM refers to inefficiencies stemming from demand

forecasting—each SCP strives to react rationally to changes in demand in their own en-

vironment which creates demand variance to the upstream of the supply chain. Bullwhip

effect in action is the easiest to comprehend through an illustration. For some reason,

demand for a certain product starts to suddenly proliferate—reasons for the surge in de-

mand, depending on the product in question—vary. In the case of, for example beer, a

successful marketing campaign, hot weather, shortages of competing and substituting

products and a plethora of other events could alone or combined result in a surge in de-

mand. Data of soaring demand is then fed into the system through a retailer or SCP in

contact with the end consumer. Lack of communication between SCPs in the chain mag-

nifies the variance of demand data as, for instance, manufacturers are not fully aware of

the new advertisement campaign initiated by the retailer. Batch order sizes vary more

radically the further SCP is located in the upstream as managers along the supply chain

attempt to respond to the growing demand by increasing their order size and create a

safety buffer for themselves. The motion of this variance of demand resembles that of a

bullwhip when cracked. (Lee et al. 1997a; 1997b.)

When the demand eventually returns to its previous levels, or below these levels, and

the peak is over, demand data travelling through the supply chain is lagging behind the

real market situation, and managers in the upstream SCPs receive information of decreas-

ing demand levels with a significant delay. All this time, production of the product af-

fected by demand fluctuations has been increased, and when the demand stabilises, stocks

of the product start to appear along the chain. In a worse-case scenario, these stocks do

not only tie up capital—which could be used more efficiently—but stocks of products

might also soon become unsaleable, especially when grocery items are in question. SCPs

34

in the supply chain engage in forecast updating i.e. companies project consumer demand

pattern based on observations. In practice, this means that companies interpret larger or-

ders as a sign of larger demand, prompting them to increase output in advance. (Lee et al.

1997a; 1997b.)

Bullwhip effect was first reported by Jay Wright Forrester in 1961 when he was dis-

cussing with the management of General Electric, an American conglomerate. The man-

agement reported notable swings in production output, inventory sizes and profits. For-

rester modelled the supply chain and realised that the closed structure of the supply chain

amplified demand variations into constant cyclic swings. Observation made by Forrester

gained prominence only 36 years later. (Forrester 1961; Lane & Sterman 2011.) In 1997,

Lee, Padmanabhan and Whang from Stanford University developed Forrester’s observa-

tion further by identifying four main causes for the bullwhip effect and ways to protect

operations from these causes in their journal article. The main causes presented were de-

mand forecast updating, order batching, price fluctuation, and rationing and shortage

gaming. (Lee et al. 1997a; 1997b.)

Order batching in short refers to the practice of postponing the placement of an order

till a certain threshold, e.g. full truckload of the ordered item, has been exceeded due to,

for example, the limited capacity of a supplier to produce and ship deliveries and better

pricing terms offered by suppliers for larger deliveries. Price fluctuation is caused by for-

ward buying agreements made between manufacturers and wholesalers/retailers. Through

these agreements, manufacturers ensure filled order books and wholesalers/retailers are

presented with lucrative price offerings. Finally, rationing and shortage gaming is a result

of manufacturer limiting a supply of a product, and when this product is in short supply,

customers exaggerate their real needs and order more. When demand levels of the product

in short supply ultimately start to decline, customers previously ordering beyond their

actual need begin to place fewer orders and cancellations start to appear. (Lee et al. 1997a;

1997b.) To combat these phenomena, Lee et al. (1997a; 1997b) propose avoiding multiple

demand forecast updates, i.e. downstream and upstream actors of a supply chain utilise

the same raw data, resupplying more frequently to avoid unusually large orders when

demand surges, that manufacturers should establish uniform wholesale pricing policies to

reduce the incentive for retailers to forward buy, and that suppliers should allocate prod-

ucts in proportion to past sales when a shortage hits. (Lee et al. 1997a; 1997b.)

Four years later Lee popularised the bullwhip effect using the notorious green-col-

oured cars case of Volvo from the 1990s as an illustration. Volvo had produced more

green-coloured cars than there was demand for. Sales and marketing team then started

substantial promotions and made special offers. These efforts bore fruit, while production

department was not aware of the promotional activities—production department inter-

preted the sales figures as a shift in customer preferences and started to assemble even

more green-coloured cars. (The Economist 2002.) Bullwhip effect can be summarised as

35

the growing volatility and inaccuracy of demand data from the downstream to the up-

stream, aggravated by the sub-optimisation of each actor along the supply chain, resulting

in misallocation of resources.

4.2 Green take on the bullwhip effect

Recently, bullwhip effect has been applied to GSCM. Klumpp (2011) was among the

first, if not the first, to use the term green bullwhip effect (GBE) in academic literature.

In his simulation, he postulates that the use of green logistics instruments—electric driven

trucks, reduction of empty tours (trucks), slow-steaming ships, use of biofuel in planes

and carbon dioxide emissions trading by airlines—predominantly have a negative effect

on the flexibility and volatility of a supply chain (Klumpp 2011). While Klumpp applies

a proactive aspect in his research and interpret GBE on his behalf to be mostly a negative

phenomenon, Lee et al. (2014) approach GBE as a reactive phenomenon with also posi-

tive repercussions.

Lee, not to be confused with previously introduced Hau L. Lee also fascinated by the

bullwhip effect, and his colleagues defined GBE as the tightening of environmental re-

quirements from the downstream to the upstream in a supply chain. Stakeholders pres-

surising the company governing the supply chain in the downstream for environmental

sustainability very often leads to GBE. Company feeling the pressure seeks to create a

safety buffer for itself by tightening the deadline for implementation of compliance

measures and relays the requirement to its first-tier supplier. Safety buffer is added in

case the supplier somehow fails to meet the requirements on time. In anticipation of future

environmental requirements from the stakeholders, company governing the supply chain

may also render the content of the requirement more stringent than original demands in

order to save effort in later. First-level supplier follows suit and tightens yet again the

requirements for its own supplier, either regarding implementation schedule, content or

both. Environmental regulations faced by SCP closest to the end consumer and by posi-

tion furthest in the upstream are of very different nature as environmental demands tighten

from succeeding to preceding tier in a similar manner order batch sizes vary in the case

of traditional bullwhip effect (Lee et al. 2014).

However, unlike the bullwhip effect, GBE can be better avoided and prepared for,

provided that all SCPs co-operate to implement the requirements according to a predeter-

mined schedule. This is often not the case due to human nature and the need of an indi-

vidual actor to optimise its operations which leads to sub-optimisation on the magnitude

of the entire supply chain. (Green et al. 2000; Lee et al. 2014.) Companies experiencing

environmental pressures respond by implementing GSCM practices. These pressures are

36

imposed by various stakeholder groups. Laari et al. (2016) identify pressure from cus-

tomer stakeholders as particularly effective in triggering the implementation of internal

GSCM practices, and thus also as a strong driver for GBE.

Lee et al. (2014) also compare bullwhip effect with its green extension and observe

that the previous is a demand-based phenomenon, whereas the latter is more random in

nature and an event-driven phenomenon. Another difference is the source of the phenom-

enon. Bullwhip effect is a systematic, built-in phenomenon in supply chains. In bullwhip

effect, every actor tries to mitigate and respond to the volatility of demand, whereas the

company being targeted by stakeholders in the downstream can intentionally trigger GBE

by implementing GSCM practices. Also, GBE does not only cause negative effect—a

toxic compound used during production of a product might be phased out prior to regu-

lative deadline due to managers creating safety buffers for themselves in the supply chain.

Another positive effect can be local spillover effects, results of co-operation between cus-

tomer and supplier SCPs as the customers, labour force and community benefit from the

supplier being a pioneer company and conducting its operations above the level of envi-

ronmental regulations. (Lee et al. 2014; Seles et al. 2016.)

However, varying opinions on the distribution of sustainability in supply chains have

been voiced in the academic discourse. Wilhelm et al. (2016) explored the double agency

role of the first-tier supplier. Due to its double agency role, first-tier supplier was postu-

lated to act as a primary agent, fulfilling the sustainability requirements of the preceding

tier in the supply chain, customer, in its own operations and secondarily, to propagate

these sustainability requirements onwards to lower-tier suppliers (Wilhelm et al. 2016).

According to the study by Wilhelm et al. (2016), the ultimate gatekeeper in ensuring the

distribution of environmental sustainability in the supply chain is the first-tier supplier,

not the company governing the supply chain. Schmidt et al. (2017) examined supply chain

position paradox, which will be presented in Chapter 4.4. Commenting on the observa-

tions made by Lee et al. (2014), Schmidt et al. (2017) propose that upstream suppliers

may be forced to overinvest into GSCM practices and may oppose the implementation of

new GSCM practices.

4.3 Social bullwhip effect—does it exist?

In the past, environmentally sustainable, or green, dimension has dominated the academic

discussion on sustainable operations. Although TBL concept encompasses also the social

aspect of sustainability, the focus of research has been more on the environmental aspect

of value-creating activities. (Klassen & Vereecke 2012; Payman & Searcy 2013; Lee et

al. 2014.) Klassen and Vereecke (2012), in their study concerning social issues in supply

chains, draw parallels between environmental and social supply chain capabilities. In

37

other words, environmental and social sustainability in supply chains have some similar-

ities, albeit environmental issues have been more widely researched in the academic field.

Lee et al. (2014) also relate environmental and social dimensions of sustainability, pro-

posing the examination of similarities and differences between environmental and social

issues in supply chains as a future research topic. A similar proposal to apply social aspect

to supply chain position paradox observed in the case of GSCM was also made by

Schmidt et al. (2017). What is already established, however, is that external stakeholder

pressure acts as a driver for enforcing both environmental and social sustainability in

supply chains (Eriksson & Svensson 2015). Lee (2011) observes that the nature and

strength of combined external stakeholder and institutional pressures, e.g. policy, cultural

norms and routines, shape the CSR strategy of an organisation. Suggestions to study the

social dimension of a phenomenon previously observed from an environmental point of

view and stakeholder pressure affecting both dimensions of sustainability provide addi-

tional justification to examine green and social bullwhip effect (SBE) as phenomena shar-

ing similar characteristics.

Asgary and Li (2016) conceived the concept of bullwhip effect due to unethical oper-

ations and, by doing this, expanded the scope of traditional bullwhip effect to include the

social dimension of conducting business. Like the case with traditional bullwhip effect,

unethical operations may engage consumers in forecast updating—however, not with de-

mand data but with the reputation of a company. First misconduct can be neglected with

little impact, but repeated offences could lead to rapid decline in consumer loyalty, which

in term has a dramatic effect on the financial bottom line of a company. (Asgary & Li

2016.)

Different from the concept of bullwhip effect due to unethical operations, SBE in this

thesis is defined as the tightening of social requirements both schedule- and content-wise

as the social demands propagate among SCPs from downstream to upstream in a supply

chain. Managers at each SCP aim to optimise their activities which leads to tighter de-

mands for the next-in-line, in parallel to how requirements are transformed in the case of

GBE. GBE can also be more prone to occur within supply chains of certain industries,

whereas SBE is more potential to appear in other industries. For example, environmental

concerns often prevail in the automotive industry while apparel industry is more charac-

terised by social issues. Another difference is that environmental violations are usually

easier to detect and measure than social ones—emissions affect the global ecosystem,

regardless of the release location, whereas a 12-hour shift might be illegal in one country

and legal in another. (Wilhelm et al. 2016.)

Very little research studying the existence of SBE in supply chains has been conducted,

and the term itself has been scarcely used in academic literature. However, as environ-

mental and social sustainability share characteristics, and although SBE has been re-

searched to a lesser extent, it does not necessarily mean SBE would not exist. What does

38

exist, is a research gap in academic literature. Such gap has also been identified by Wang

and Disney (2016) who call for further research to complement traditional and green bull-

whip effect by other forms or extensions of the phenomena, and especially from the sus-

tainability point of view.

A concrete example of social sustainability pressure from stakeholders—in this case,

from legislators—that could set off SBE, is the Dodd-Frank Wall Street Reform and Con-

sumer Protection Act (Dodd-Frank Act), verified by the Obama regime in July 2010

(Dodd-Frank Wall Street Reform and Consumer Protection Act 2010). This act has re-

cently addressed the issues concerning the so-called conflict minerals which are mainly

being extracted in the Democratic Republic of Congo. The extraction and trading process

of conflict minerals in the Democratic Republic of Congo is partially controlled by armed

groups, which commit atrocities against basic human rights. (Global Witness 2014.) Ini-

tiatives analogous to the Dodd-Frank Act require supply chains to be cleared of minerals

with dubious origins, thus acting as potential impetus to trigger SBE. Companies like LG

governing the supply chain have issued sustainability policies or joined sustainability

schemes to eradicate conflict minerals from their supply chains, and by doing this, poten-

tially set off SBE. (LG 2013; Hofmann et al. 2018.)

4.4 Supply chain position paradox

In their research, Schmidt et al. (2017) apply the concept of SCP to study the relationship

between implementation and effects of GSCM practices. The outcome was that although

every SCP in the supply chain does benefit from GSCM practices, the benefit gained

diminishes the closer SCP is located to the end consumer. The study also highlights that

the closer an SCP is to the end consumer, the more GSCM practices the company in that

SCP performs. Schmidt et. al. (2017) named this phenomenon supply chain position par-

adox. What explains the diminishing marginal utility of GSCM practices, when the prox-

imity of SCP to the end consumer increases, is the maturity of the GSCM practices im-

plemented. Companies governing supply chains and companies in general located in the

downstream have been under stakeholder pressure and public scrutiny from early on

which has led them to already have “reaped the low-hanging fruits” by implementing

GSCM practices with direct efficiency and market performance yields in an early adopter

position (Delmas & Montiel 2009: Siegel 2009). Same companies implement more ma-

ture GSCM practices which affect processes rather than result in immediate outcomes.

Improvements in process performance actualise with a delay, and thus cannot be show-

cased with the same tempo as the earlier GSCM yields of less mature practices. (Darnall

& Edwards 2006; Busch & Hoffmann 2011; Schmidt et al. 2017.)

39

However, to overcome the burden of being in the ungrateful SCP close to the end

consumers and most visible to stakeholders, companies in this position should take a more

proactive stance towards involvement of stakeholders in operations according to Schmidt

et al. (2017). Although consumer stakeholders pose requirements for high levels of envi-

ronmental sustainability for original equipment manufacturer (OEM) and retailer opera-

tions, this does not always materialise into purchasing decisions. Stakeholders instead

should be more involved in the operations of the entire supply chain. (Aragón-Correa &

Sharma 2003; Buysse & Verbeke 2003; Ateş et al. 2012; Schmidt et al. 2017.) Some

stakeholders possess certain expertise which can be utilised to formulate more considerate

sustainability objectives, and which can aid in implementing GSCM practices throughout

the supply chain (Manetti & Toccafondi 2012; Gualandris et al. 2015). To enhance the

involvement of stakeholders in operations along the entire supply chain, stakeholders with

expertise are to be recognised and treated as valuable members of the value-creating eco-

system—not as an external party (Schmidt et al. 2017).

In previous research, it has been stated that many of the lower-tier suppliers administer

issues of environmental and social sustainability passively, thus posing the largest and

most probable risk of sustainability misconduct in the supply chain (Plambeck 2012; Vil-

lena & Gioia 2018). The passiveness in addressing sustainability issues can also be ex-

plained by the lower level of scrutiny stakeholders are imposing on these lower-tier, less

visible companies (Chiu & Sharfman 2011; Schmidt et al. 2017).

40

5 HYPOTHESES DEVELOPMENT

Previous research on the distribution of environmental and social sustainability between

SCPs and between different industries has been scarce. GBE has been studied most nota-

bly by Klumpp (2011; 2019), Lee et al. (2014), Klumpp et al. (2016) and Seles et al.

(2016)— very little research on SBE has been conducted. Pioneering studies by Lee et al.

(2014) and Seles et al. (2016) support the existence of GBE and consider the possible

positive effects of GBE e.g. more sustainably aware and greener supply chains. Klumpp

(2011) and Klumpp et al. (2016), in contrast, interpret GBE as a predominantly negative

phenomenon having a deteriorating impact on supply chain flexibility and volatility in

form of excess flexibility costs. Klumpp (2019) also expanded his interpretation of GBE

to sustainable lifestyles. Study by Villena and Gioia (2018), in turn, concluded that lower-

tier suppliers in the upstream of supply chains are most likely to treat environmental and

social issues passively and are the most probable to cause misconduct. Villena and Gioia

(2018), however, included supply chains stretching beyond European borders into emerg-

ing economies within their sample, thus gaining better insight on the operations of lower-

tier suppliers. For this research, the examination of environmental and social sustainabil-

ity distribution in supply chains is combined with the study on both GBE and SBE.

In this thesis, it is postulated a priori that GBE exists as proven by Lee et al. (2014)

and Seles et al. (2016) in their case research and statements made by Klumpp (2011;

2019) and Klumpp et al. (2016) are critically contemplated. Lee et al. (2014) examined

three different supply chain cases with the scope of three SCPs—OEM and the first two

tiers of suppliers—in electronics and fashion apparel industries. They concluded that en-

vironmental requirements, which are converted into GSCM practices, tighten along the

supply chain from the downstream towards the upstream, and at the upstream, yield spill-

over benefits for local customers, workers and communities. Data was collected through

interviewing managers at case companies and by utilising archival material, capturing

longitudinal information unavailable to the public, and published organisational docu-

ments. (Lee et al. 2014.)

Seles et al. (2016), on their behalf, while referring to research by Lee et al. (2014),

focus on institutional and stakeholder theory in terms of pressure exertion on manufac-

turing supply chains. Seles et al. (2016) studied the distribution of environmental require-

ments and GSCM practices in a Brazilian automotive battery supply chain. Extending the

scope to four SCPs compared to the study by Lee et al. (2014), Seles et al. (2016) exam-

ined a supply chain consisting of OEM “Alpha” (manufacturer of automotive batteries),

Alpha’s customer (a heavy vehicle manufacturer), Alpha’s main supplier of plastic com-

ponents, and CETESB, a governmental body responsible for controlling, inspecting, mon-

itoring and licensing pollution-generating activities. CETESB exerts pressure on Alpha’s

customer and thus triggers GBE. Primary data was gathered through interviews and direct

41

observations made at the studied organisation—organisational documents, reports, man-

uals, procedures, website information—served as a source of secondary data. Environ-

mental pressures were found to propagate along a supply chain from SCP to SCP, from

downstream towards upstream. The end customer, heavy vehicle manufacturer in the case

study, received environmental pressure from the governmental body CETESB, which set

GBE in motion. Environmental requirements then got tightened both in content and/or in

terms of implementation deadlines from SCP to SCP as each actor in the chain relayed

pressure forward to the next-in-line, magnifying GBE with each transition of pressure.

(Seles et al. 2016.)

Hypotheses H1a and H2a are formulated based on the results by both Lee et al. (2014)

and Seles et al. (2016). Hypotheses for the assessment of environmental and social sus-

tainability distribution between SCPs are:

• H1a. Environmental sustainability distributes between SCPs according to

green bullwhip effect—statistically significant differences exist between

environmental sustainability scores of SCPs.

• H1b. Social sustainability distributes between SCPs according to proposed

social bullwhip effect—statistically significant differences exist between social

sustainability scores of SCPs.

Research on how industry affects sustainability has been chiefly conducted as case

studies. For example, food, fashion and biofuel industries have been a subject of multiple

sustainability studies. In case of food industry, for example Yakovleva et al. (2012) com-

pared environmental, social and economic sustainability of different food industry supply

chains, Beske et al. (2014) studied SSCM practices and dynamic capabilities in food in-

dustry and Grimm et al. (2014) examined environmentally and socially critical factors for

lower-tier supplier management in food supply chains. Sustainability in biofuels industry,

in turn, has been explored by e.g. Walter et al. (2011), Gaurav et al. (2017) and Cardoso

et al. (2019), whereas sustainability of fashion industry has been the research topic of, for

example, Caniato et al. (2012), Shen (2014) and Turker and Altunas (2014). Comparisons

of sustainability between industries, however, have been scarce in the academic field.

Commonly, such comparisons are limited to only a few industries, e.g. oil and gas and

tyre manufacturing industries by Mani et al. (2015), catalytic converter and platinum jew-

ellery industries by du Plessis and Bam (2018), manufacturing, agriculture, services and

chemical industries by Singh et al. (2016). Such researches are oftentimes case studies,

as well.

Concept of sustainable manufacturing (SM) according to Moldavska and Velo (2012)

is becoming increasingly mature. Nonetheless, Moldavska and Velo (2012) conclude that

inconsistencies in the interpretation of SM issues result in lack of unified terminology and

vocabulary, and that a unified understanding of SM concept has not yet been reached.

These observations resemble ones made by Van der Leeuw et al. (2012), Bursztyn and

42

Drummond (2014) and Bansal and Song (2017) regarding the field of sustainability sci-

ences not having reached maturity. The small number of studies on the effect of industry

on sustainability, let alone benchmarking manufacturing industries, might be, to some

extent, explained by the immaturity of associated research fields, which calls for explo-

ration of the correlation between environmental and social sustainability and industry.

Hypotheses for the assessment of environmental and social sustainability distribution

between industries are:

• H2a. Industry affects environmental sustainability—statistically significant

differences exist between environmental sustainability scores of different

industries.

• H2b. Industry affects social sustainability—statistically significant

differences exist between social sustainability scores of different industries.

If the hypotheses are supported according to the results of this thesis, further evidence on

the existence of GBE and arguments for the existence of SBE are provided. Industry af-

fecting environmental and social sustainability would also be affirmed.

43

6 METHODOLOGY

6.1 Methodological approach

This research can be easily positioned in the framework developed by Neilimo and Näsi

(1980) and later supplemented by Kasanen et al. (1993). Business research methodologies

framework examines the theoretical-practical trade-off and the aim of the research—is

the research striving to introduce a phenomenon in “as-is” state or is the aim of the re-

search to improve the situation at hand, say, suggest a process improvement (Vafidis

2007). On a visualisation of this framework, nomothetical approach in the intersection

point between descriptive and empirical research is the most fitting approach for the re-

search conducted in this thesis, illustrated in Figure 3.

Note Research approach chosen for this thesis highlighted in red

Figure 3 Business research methodologies of the Neilimo and Näsi framework

supplemented by Kasanen et al. (adapted from Neilimo and Näsi 1980;

Kasanen et al. 1993; Vafidis 2007)

Nomothetical research approach is characterised by the prevalence of positivism—

knowledge is generated by making immediate, empirical observations and applying a

stringent scientific method on these observations. According to positivism, knowledge is

objective in nature, irrelevant of the observer—when conducting nomothetical research,

statistical analysis is oftentimes chosen to serve as the method of analysis. (Neilimo &

Näsi 1980; Kasanen et al. 1993; Vafidis 2007.) Testing hypotheses on self-collected data

in order to better understand the distribution of sustainability within supply chains is nom-

othetical research at its purest.

44

The ninefold framework by Arbnor and Bjerke (1997) combines the method of gener-

ating knowledge (objective-subjective) with the method of analysis used. According to

this framework, an analytical approach (statistical company data from a database) applies

to the research conducted in this thesis as analysis of variance was chosen as the method

of analysis. Arbnor and Bjerke framework is illustrated in Figure 4.

Note Research approach and main method chosen for this thesis illustrated

with a red star

Figure 4 Visualisation of research approaches and main methods in the Arbnor,

Bjerke and Vafidis framework (adapted from Arbnor & Bjerke 1997;

Vafidis 2007)

Whereas the model developed by Neilimo and Näsi (1980) is more oriented towards

assessing the methodological approach and the scope of both practical and theoretical

dimensions emphasised by the research, the framework of Arbnor and Bjerke (1997) ex-

amines the research perspective. These perspectives are the subjective one aiming at con-

ducting verstehen-type research and the objective one with the intention to explain the

research phenomenon. Arbnor and Bjerke (1997) divide main research methods into three

categories: analytical, systems and actors approach. Analytical approach is the most pos-

itivist one, and thus does not need, nor desire for, subjective human interference in the

knowledge production process. Characteristic for this approach is interest in causal rela-

tions and that the research object can be split into parts and studied independently of each

other—this approach is also the most fitting to describe the research approach of this

thesis. Systems approach does not allow the independent examination of parts of a sys-

tem. Maintaining positivist traits, this approach may also include hermeneutic type of

research. Actors approach is a highly subjective research method where research cannot

be accessed objectively. Without interpretations of individuals, there is no research when

this approach is applied. (Arbnor & Bjerke 1997; Vafidis 2007.)

45

6.2 Data source

For this research, ESG data provided by Thomson Reuters (TR) has been utilised. Eikon

was chosen as the data source due to ease of accessibility, as University of Turku has a

license for the database, and due to the size of the database. Eikon database offers ESG

scores of over 7,000 companies. To better understand the hierarchy and the structure of

ESG scoring by TR, and illustration of ESG scores, pillars and categories is demonstrated

in Figure 5 to support the description of the ESG scoring process at TR.

46

Figure 5 Thomson Reuters ESG scoring (adapted from Thomson Reuters 2018)

47

150 content research analysts working at TR collect data from six different sources:

websites of companies, annual reports, CSR reports, stock exchange filings in addition to

NGO websites and news sources. The ESG data extraction process at TR utilises both

algorithmic and human methods and the data is refreshed every fortnight, while the ma-

jority of ESG data reported is updated in parallel with companies’ own ESG publication

once a year. Data is collected through 178 measures which form 10 categories and which,

on their behalf, form three pillars. These measures can be in form of a question answered

with “true” or “false”—“does the company have a policy to improve its energy effi-

ciency?”—or in a form quantitative indicator—"percentage of employees with disabilities

or special needs”. The entire list of environmental and social measures applied in this

research is illustrated in Appendices 1 and 2. An ESG score can be calculated for a com-

pany by utilising the three pillars, environmental, social and governance. TR ESG scoring

places an additional emphasis on any notable controversies the company has endured

during its accounting year. By applying ESG score and controversies score, a final ESG

combined score can be calculated. (Thomson Reuters 2018.)

For this research, focus will be on two pillar scores, environmental and social. Contro-

versies scores have been omitted from the data sample as some of the measures used to

calculate controversies scores are already used for calculating environmental and social

pillar scores. Practice of including controversies scores would imply the duplication of

some data in the analysis as well as an addition of a score based on a slightly different

methodology than that of environmental and social scores. In a similar vein, corporate

governance pillar and its measures have been excluded from this research as these

measures evaluate intra-company-related performance and harmonising these measures

with social measures would have been an arduous and convoluted process adding little

value to this research. Even though governance measures include several social sustaina-

bility measures e.g. sustainability compensation incentives, board gender diversity in per-

centages and CSR sustainability reporting, only a fragment of these 101 measures are

purely social sustainability related. Substituting measures for the omitted governance

ones can be found among social measures.

In order to achieve a sufficient geographical, industrial and company size diversifica-

tion among the sample companies, a suitable index was chosen. STOXX® Europe 600

(STOXX 600) constitutes of small, medium and large capitalisation companies from 17

European nations ranging widely in terms of industrial activity (STOXX 2018).

48

6.3 Data collection & sampling

TR has categorised Eikon companies according to Thomson Reuters Business Classifica-

tion (TRBC) which stands comparison with the classification used for STOXX 600, In-

dustry Classification Benchmark of FTSE Russell. Unlike TRBC, Industry Classification

Benchmark classification follows the hierarchy industry-supersector-sector-subsector,

whereas TRBC categorises companies in a more detailed manner, economic sector-busi-

ness sector-industry group-industry-activity. (FTSE Russell 2018; TRBC 2018.)

Before extraction of ESG data, a sample of companies conducting industrial activities

fitting into a manufacturing supply chain framework—operations of the company consist

of value chain activities transforming physical resources into a physical product with a

demand—was chosen. Some industries were identified with relative ease to be ill-fitting

for the sample, e.g. banking services, insurance, software and IT services as no physical

product is involved in their core business activities, others due to the lack of any trans-

formation of a physical product (transportation services).

However, there were also ambiguous and less distinct industries which did not have

one single field of operations, e.g. construction and engineering, environmental services

and equipment, industrial conglomerates. The operations of some companies did not un-

conditionally fit into their assigned industry and had to be examined individually—e.g.

the industry of dormakaba Holding AG on Eikon is reported to be communications and

networking, while the company provides physical products e.g. entrance system solu-

tions, door hardware and mechanical key systems (dormakaba 2018). Due to the complex

nature of value-creating operations of certain companies, e.g. conglomerates, a criterion

was set that over 50 % of the company’s revenue must be generated from manufacturing

or operations related to manufacturing in the supply chain, such as retail of physical prod-

ucts.

The company sample consists of 290 companies, of which desired ESG data—envi-

ronmental and social pillar scores—were available from reporting year 2017. Same year

was used for all companies to harmonise the data. Lorentz et al. (2016a) developed a

fourfold value/supply chain model which elaborates the activities of each SCP and sim-

plifies often complex supply chains on a theoretical level. For this research, the number

of SCPs was dropped to three—manufacturer 1 (M1), manufacturer 2 (M2) and vendor

(V). SCPs and sample sizes are illustrated in Figure 6. The initial division comprised four

SCPs, but wholesaler and retailer SCPs had to be merged into vendor SCP as the number

of wholesaler companies with desired ESG data available from 2017 was very small, only

15 companies, in the end. In previous research, Schmidt et al. (2017) also treated distrib-

utors and retailers as a single SCP.

49

Figure 6 Division of SCPs utilised in this research, sample size in parentheses

(adapted from Lorentz et al. 2016a)

Value-creating activities of companies identified as manufacturer 1 include e.g. basic

resource extraction like mining minerals, production of industrial gases and semiconduc-

tors manufacturing. If an SCP of a company is manufacturer 2, the said company produces

end products such as vehicles, apparel and pharmaceuticals. Vendor position combines

two supply chain activities, wholesaling and retailing. All activities of the three SCPs are

related to the transformation of physical resources into a more valuable physical product

which has a demand, i.e. service supply chains in industries such as bank and insurance

sector and healthcare services have been omitted from this research.

Eikon was searched for all European wholesale and retail companies with ESG data

available from 2017, and 28 companies outside of STOXX 600 index were added to the

sample in order to increase the data mass. In addition to division to SCPs, companies were

also divided between five industries, a division adapted from Lorentz et al. (2016b), with

the sample size in parentheses:

• process industry—food and drink, wood, paper, chemical and pharma

(113 companies)

• light industry—textile and apparel, rubber and plastic, mineral products and

furniture (77 companies)

• metal refining and metal products (16 companies)

• machines, appliances and transport equipment (59 companies)

• computers and electronics (25 companies).

Division to industries was performed based on revenue—industry was chosen to match

the activity generating the largest revenue within the company. Industry-based division

was done to allow comparisons between the environmental and social sustainability

scores of different industries. The sample did not evenly distribute between the industries

as process and light industries were dominant ones in sample sizes. Complete sample

company list, their SCP, TRBC-classified activity and industry have been illustrated in

Appendices 3, 4 and 5.

50

6.4 Data analysis

To determine if statistically significant differences exist between the ESG data of differ-

ent SCPs and industries, one-way analysis of variance (ANOVA) was chosen as the sta-

tistical model. F-test and Welch’s test were consequently chosen as suitable methods of

statistical analysis as by comparing group means and stating if statistically significant

differences exist or not, hypotheses are supported or rejected. If either test demonstrates

p-values higher than the significance level of 0.05—chance of error is 5 %—the chance

of error increases excessively, and thus the tested hypothesis must be rejected. (Hair et al.

2010.)

In this research, two sets of means were calculated based on ESG data. Group means

based on each SCP and industry, illustrated in Tables Table 4Table 5, were calculated for

three environmental categories, four social categories, and environment and social pillar

aggregating their respectable categories. Aggregated environmental and social sustaina-

bility category and pillar scores of sample companies were defined as the dependent var-

iable and SCP and industry as the independent variable. Group means were then com-

pared to detect statistically significant differences to either support or reject the hypothe-

ses.

6.5 Validity and reliability of the research

Two properties ensure that research has been conducted in a legitimate manner, according

to the standards of the scientific community. These two properties are validity and relia-

bility. The first one evaluates the appropriateness of the chosen instrument for measuring

the researched phenomenon, i.e. instrument measures what it sets out to measure. Relia-

bility, in turn, determines if an instrument can be consistently interpreted in different sit-

uations—in other words, how well the measurement yields trustworthy results instead of

random ones.

In this quantitative research, levels of environmental and social sustainability of dif-

ferent companies were of interest. By using ESG scores reflecting environmental and

social sustainability of a company, the distribution of both dimensions of sustainability

between SCPs and certain industries can be assessed. Using ESG data generated by a

large, distinguished financial data provider, the market share of Thomson Reuters was

22.5 % in 2017, is one way to ensure that applied data is reliable (Murphy 2018). TR also

proclaims to have one of the largest ESG content collection operations in the world with

150 content research analysts (Thomson Reuters 2018). The selection of data ranking

companies based on environmental and social criteria matches superbly with the aim of

51

this research to explore the distribution of environmental and social sustainability be-

tween SCPs and industries. As Thomson Reuters has been publishing ESG data since

2002 and continues to widen their coverage of different industries and regions by adding

new companies through different indices, TR also has vast experience in providing sus-

tainability data overall (Thomson Reuters 2018).

Reliability of this research is relatively high as TR updates ESG data constantly and

by obtaining the updated company list from the newest version of the STOXX 600 index,

this research can be replicated to the highest degree. ESG data by TR has also been uti-

lised in multiple previous studies by e.g. Cheng et al. (2014), Sassen et al. (2016) and

Garcia et al. (2017).

52

7 RESULTS

7.1 Assumptions of ANOVA tests

Hypotheses were defined to explore the distribution of environmental and social sustain-

ability in manufacturing supply chains. Hypotheses were derived from research questions

and were based on the division of sample companies into SCPs and industries. H1a and

H1b support the claim that statistically significant differences in environmental and social

sustainability distribution between SCPs exist, while hypotheses H2a and H2b claim the

same for industries. In this thesis, the existence of green and social bullwhip effect were

also studied, of which the latter’s existence has been scarcely studied in the academic

realm. The existence of GBE posits essentially on the observations made by Lee et al.

(2014) and Seles et al. (2016). The research conducted in this thesis extends the scope of

SCPs examined to include wholesale and retail activities in comparison to studies by Lee

et al. (2014) and Seles et al. (2016). The results were anticipated to support the existence

of both green and social bullwhip effect. This would imply that companies in the upstream

would rank, on average, higher in terms of environmental and social pillar and category

scores than the companies located in the downstream closer to the end customer.

In order to conduct one-way ANOVA tests to examine, if statistically significant dif-

ferences exist between the group means of SCPs and industries, certain assumptions need

to be made. Variables need to be independent and identically distributed, data must be

normally distributed, i.e. dependent variable is normally distributed in the population, and

variables are homoscedastic, in other words, the variances of values are the same in each

sub-population. First assumption concerning independent observations can be made as all

category and pillar scores are representing 290 individual companies. Second assumption

of normally distributed data in each population can be tested by examining the skewness

and kurtosis of each population which are here named groups, categories and pillars. (Hair

et al. 2010.)

Skewness measures the symmetry of data in a population, in this research comparing

it to normal distribution. Skewness can obtain both negative and positive values—posi-

tively skewed distribution is composed of relatively few large values and tails to the right,

whereas negatively skewed distribution contains few small values and tails to the left.

Kurtosis examines either the flatness or the peakedness of a distribution compared to nor-

mal distribution. The higher the value of kurtosis, the more peaked the distribution is,

while a negative value indicates a rather flat distribution. (Hair et al. 2010.) The results

of skewness and kurtosis tests for each population are presented in Table 1.

53

Table 1 Testing the normal distribution assumption of data between groups

Categories & pillars N Minimum Maximum Mean Std.

deviation

Skewness Kurtosis

Statistic Std. error Statistic Std. error

ENVIRONMENT 290 13.4 99.4 70.9 17.5 −0.816 0.143 0.627 0.285

Resource Use 290 11.7 99.8 76.4 19.5 −1.044 0.143 0.863 0.285

Emissions 290 1.39 99.8 72.6 22.2 −1.044 0.143 0.577 0.285

Innovations 290 0.29 99.8 63.6 26.6 −0.463 0.143 −0.979 0.285

SOCIAL 290 11.1 98.8 70.4 17.1 −0.855 0.143 0.837 0.285

Workforce 290 10.6 99.8 73.4 19.6 −0.806 0.143 0.030 0.285

Human Rights 290 15.8 99.6 77.8 22.5 −1.261 0.143 0.638 0.285

Community 290 0.68 99.8 62.1 28.4 −0.371 0.143 −1.075 0.285

Product Responsibility 290 1.39 99.8 68.3 25.8 −0.818 0.143 −0.272 0.285

The skewness and kurtosis values of groups varied in the case of skewness [−1.261, −0.371] and kurtosis on the range [−1.075, –0.863]. This

indicates that groups tend to contain few small values and tail to the left, whereas the distributions of groups, on average, are more peaked in appear-

ance than flat, although two clearly flat distributed groups can be observed. The acceptable value range to make the normal assumption required for

ANOVA is up for debate. For this research, the range of acceptable values for both skewness and kurtosis to support normal distribution assumption

is [−2, 2] (George and Mallery 2010). Data fulfils the normal distribution assumption and, ultimately, needs to be tested for homoscedasticity.

Levene’s test examines whether population has the same variance in each group or not. Levene’s tests results for SCP comparison are visualised in

Table 2 and for industries in Table 3.

54

Table 2 Testing the assumption of homoscedasticity with Levene’s test,

comparisons between SCPs

Categories & pillars Levene

statistic df1 df2

Significance

(p)

ENVIRONMENT 7.193 2 287 0.001

Resource Use 4.587 2 287 0.011

Emissions 5.923 2 287 0.003

Innovations 5.980 2 287 0.003

SOCIAL 1.294 2 287 0.276

Workforce 0.567 2 287 0.568

Human Rights 5.310 2 287 0.005

Community 0.654 2 287 0.521

Product Responsibility 11.28 2 287 0.000

Note Groups, where variances are equal, are bolded

The assumption of homoscedasticity can be made with social pillar, workforce and

community categories based on Levene’s test in the case of SCP comparison. If the sig-

nificance value of a group exceeds the threshold of 0.05, variances are equal and thus the

assumption of homoscedasticity can be made. However, for the environment pillar and

rest of the categories where variances are not equal, Welch’s test needs to be made instead

of f-test to compare the group means.

Table 3 Testing the assumption of homoscedasticity with Levene’s test,

comparisons between industries

Categories & pillars Levene

statistic df1 df2

Significance

(p)

ENVIRONMENT 1.341 4 285 0.255

Resource Use 1.115 4 285 0.350

Emissions 0.445 4 285 0.776

Innovations 2.933 4 285 0.021

SOCIAL 1.825 4 285 0.124

Workforce 0.518 4 285 0.723

Human Rights 2.297 4 285 0.059

Community 3.314 4 285 0.011

Product Responsibility 1.037 4 285 0.388

Note Groups, where variances are equal, are bolded

55

In the case of assumption of homoscedasticity between industry groups, all signifi-

cance values of groups exceed the threshold excluding innovations and community cate-

gories which need to be examined with Welch’s test instead of the f-test.

7.2 Results of hypotheses testing

According to previous studies on GBE by Lee et al. (2014) and Seles et al. (2016), the

company governing the supply chain located at the downstream of the chain shifts the

pressures, in form of environmental requirements imposed by stakeholders, onwards in

the supply chain to the preceding SCP, the tier next-in-line. Environmental requirements

become more stringent with each shift towards upstream, as each company at every SCP

attempts to optimise their own operations, simultaneously failing to optimise the entire

supply chain. SBE acts the same. Instead of environmental requirements, demands for

social reforms, e.g. conducting ethical trade and combatting bribery, corruption and fraud,

are shifted towards upstream. Requirements for social reforms become more stringent

along the way, implementation schedule- and/or content-wise.

Hypotheses H1a and H1b were supported to a certain degree by the results of ANOVA

tests when SCPs were compared. As the p-values remained under the significance level

of 0.05 in eight group mean comparisons, two pillars and six categories, statistically sig-

nificant differences were discovered. Hypothesis H1b could not be supported regarding

the workforce category—for this category, statistically significant differences do not exist

between SCP scores, and thus comparison based on this category does not support the

existence of SBE. Ergo, this category is excluded from the following analysis. Results of

the ANOVA tests are illustrated in Table 4 and Table 5.

56

Table 4 Results of ANOVA tests, distribution of environmental and social sustainability between SCPs

Categories & pillars Group means F-

statistic

Significance

(p) M1 M2 V Total

Test: F-test ANOVA

SOCIAL 72.5 73.7 61.2 70.4 13.38 0.000

Workforce 72.7 75.9 70.9 73.4 1.487 0.228

Community 68.3 66.9 42.7 62.1 22.43 0.000

Test: Welch's ANOVA

ENVIRONMENT 72.7 73.0 64.2 70.9 4.370 0.014

Resource Use 77.1 80.7 68.4 76.4 6.477 0.002

Emissions 71.7 77.3 66.7 72.6 4.496 0.013

Innovation 69.3 60.6 57.3 63.6 5.562 0.005

Human Rights 81.0 80.5 67.4 77.8 7.316 0.001

Product Responsibility 71.3 72.3 56.3 68.3 6.846 0.001

Note SCP abbreviations used are as follows:

M1 Manufacturer 1 (raw materials and components)

M2 Manufacturer 2 (end products)

V Vendor (wholesale and retail)

Group mean comparisons supporting the hypotheses about the existence of scientifically significant differences in sustainability

distribution between SCPs bolded

57

Table 5 Results of ANOVA tests, distribution of environmental and social sustainability between industries

Categories & pillars Group means F-

statistic

Significance

(p) P L Me Ma C Total

Test: F-test ANOVA

ENVIRONMENT 69.6 71.9 71.3 71.4 72.1 70.9 0.255 0.907

Resource Use 76.4 77.9 77.5 73.8 77.7 76.4 0.426 0.790

Emissions 71.4 74.2 80.7 70.7 71.8 72.6 0.826 0.509

SOCIAL 72.1 69.6 72.8 67.6 70.1 70.4 0.799 0.527

Workforce 74.5 74.4 76.7 69.1 73.6 73.4 0.980 0.419

Human Rights 78.4 78.6 84.4 74.6 75.6 77.8 0.755 0.556

Product Responsibility 72.2 65.7 60.4 66.9 66.9 68.3 1.275 0.280

Test: Welch's ANOVA

Innovation 60.9 63.4 54.9 69.8 66.7 63.6 1.804 0.138

Community 63.7 58.4 69.2 61.5 62.8 62.1 0.707 0.590

Note Industry abbreviations used are as follows:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

58

When comparing group means of five different industries, ANOVA test results indi-

cate no statistically significant differences between any of the group means as chance of

error is systematically over the allowed threshold of 5 %—p-values in two pillar and

seven categories comparison exceed the threshold value of 0.05 of significance level sub-

stantially. It must be thus established that industry does not affect the distribution of en-

vironmental and social sustainability according to this research.

7.3 Results of post hoc tests

The post hoc tests used were Tamhane’s T2 and Tukey HSD. Post hoc tests are always

trade-offs between controlling type I error or type II error. When a test is aiming to control

type I error, i.e. a deduction is made that two means are statistically significantly inequal,

the test is called conservative. When a test possesses statistical power, it is suited for

controlling type II error—a situation where a deduction is made that two means are not

statistically significantly inequal. Both tests, Tamhane and Tukey, are conservative.

(Field 2018.) Tamhane was used in comparisons where group variances were equal ac-

cording to Levene’s test, whereas Tukey HSD was chosen when variances were not equal.

Results of post hoc tests are presented in Tables Table 6, Table 7, Table 8Table 9.

Table 6 Post hoc test p-values for group mean comparisons between SCPs

Categories & pillars Manufacturers

compared

Vendor

compared with

M1 M2

Post hoc test: Tamhane

ENVIRONMENT 0.998 0.020 0.018

Resource Use 0.323 0.032 0.001

Emissions 0.112 0.484 0.021

Innovation 0.040 0.014 0.843

SOCIAL 0.908 0.000 0.000

Human Rights 0.996 0.001 0.003

Product Responsibility 0.985 0.003 0.002

Post hoc test: Tukey HSD

Workforce 0.428 0.819 0.233

Community 0.913 0.000 0.000

Note Values bolded are less than the significance level of 0.05, meaning that

statistically significant differences in means between the compared SCPs

exist in the given category/pillar

59

The results of post hoc tests between environmental and social sustainability of group

means of SCPs reveal that statistically significant differences exist between the manufac-

turer 1 and manufacturer 2 SCPs in the innovation category—this was the only group

where a statistically significant difference was observed between the manufacturers.

When both manufacturer SCPs are compared with the vendor SCP, statistically signifi-

cant differences are detected in almost every category and pillar. As a matter of fact, only

when group means are compared between manufacturer 1 and vendor in the emissions

category and between manufacturer 2 and vendor SCPs in the innovation category, no

statistically significant differences were detected. Between workforce category group

means, as previously established with f-test, no statistically significantly differences exist.

60

Table 7 Post hoc test p-values for group mean comparisons, process and light industries

Categories & pillars Compared with process industry Compared with light industry

L Me Ma C P Me Ma C

Post hoc test: Tamhane

Innovation 0.999 0.993 0.245 0.987 0.999 0.933 0.755 1.000

Community 0.911 0.995 1.000 1.000 0.911 0.764 1.000 0.999

Post hoc test: Tukey HSD

ENVIRONMENT 0.903 0.996 0.969 0.971 0.903 1.000 1.000 1.000

Resource Use 0.983 0.999 0.923 0.998 0.983 1.000 0.734 1.000

Emissions 0.918 0.521 1.000 1.000 0.918 0.822 0.894 0.990

SOCIAL 0.858 1.000 0.472 0.984 0.858 0.961 0.962 1.000

Workforce 1.000 0.994 0.415 1.000 1.000 0.993 0.512 1.000

Human Rights 1.000 0.854 0.828 0.980 1.000 0.881 0.838 0.977

Product Responsibility 0.433 0.431 0.700 0.888 0.433 0.946 0.999 1.000

Note Industry abbreviations used are as follows:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

61

Table 8 Post hoc test p-values for group mean comparisons, metal refining and metal products and machines,

appliances and transport equipment industries

Categories & pillars

Compared with metal refining and

metal products

Compared with machines,

appliances and transport

equipment

P L Ma C P L Me C

Post hoc test: Tamhane

Innovation 0.993 0.933 0.371 0.846 0.245 0.755 0.371 1.000

Community 0.995 0.764 0.970 0.996 1.000 1.000 0.970 1.000

Post hoc test: Tukey HSD

WENVIRONMENT 0.996 1.000 1.000 1.000 0.969 1.000 1.000 1.000

Resource Use 0.999 1.000 0.961 1.000 0.923 0.734 0.961 0.916

Emissions 0.521 0.822 0.499 0.719 1.000 0.894 0.499 1.000

SOCIAL 1.000 0.961 0.820 0.988 0.472 0.962 0.820 0.973

Workforce 0.994 0.993 0.641 0.989 0.415 0.512 0.641 0.865

Human Rights 0.854 0.881 0.529 0.736 0.828 0.838 0.529 1.000

Product Responsibility 0.431 0.946 0.902 0.934 0.700 0.999 0.902 1.000

Note Industry abbreviations used are as follows:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

62

Table 9 Post hoc test p-values for group mean comparisons,

computers and electronics industry

Categories & pillars

Compared with computers and

electronics

P L Ma Me

Post hoc test: Tamhane

Innovation 0.987 1.000 0.846 1.000

Community 1.000 0.999 0.996 1.000

Post hoc test: Tukey HSD

ENVIRONMENT 0.971 1.000 1.000 1.000

Resource Use 0.998 1.000 1.000 0.916

Emissions 1.000 0.990 0.719 1.000

SOCIAL 0.984 1.000 0.988 0.973

Workforce 1.000 1.000 0.989 0.865

Human Rights 0.980 0.977 0.736 1.000

Product Responsibility 0.888 1.000 0.934 1.000

Note Industry abbreviations used in the appendix:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

In comparison between industries, no statistically significant differences were detected

between any of the industries in any category or pillar as demonstrated in Tables Table

7,Table 8 andTable 9.

In all eight comparisons, where statistically significant differences were present, the

vendor position received the lowest scores. The scores range 0–100 where 100 is the best

possible score. Score differences are illustrated in Table 10. The average score gap be-

tween both manufacturing SCPs in comparison to the vendor SCP, is discernible, which

initially affirms the existence of both green and social bullwhip effect to a certain degree.

The average score differences between vendor and manufacturer 2 were 12.6 and 12.4

between vendor and manufacturer 1, both in favour of the manufacturing SCPs.

63

Table 10 Score differences between SCPs, workforce category excluded

Categories & pillars Manufacturer

2 vs. vendor

Manufacturer

1 vs. vendor

Manufacturer 1

vs. manufacturer

2

ENVIRONMENT 8.78 8.42 −0.36

Resource Use 12.3 8.67 −3.64

Emissions 10.5 4.97 −5.58

Innovation 3.32 11.9 8.62

SOCIAL 12.5 11.3 −1.26

Human Rights 13.0 13.6 0.57

Community 24.2 25.6 1.45

Product Responsibility 16.0 15.04 −0.96

Average 12.6 12.4 −0.15

Note The score subtraction was made from SCP mentioned first in the column.

For example, vendor’s average score in the environment pillar was 64.24

and corresponding score of manufacturer 2 was 73.02, so the subtraction

equals 8.78

However, according to both green and social bullwhip effect, ESG scores should no-

ticeably improve when moving towards upstream in the supply chain. This was not the

case as differences in scores were, in both environmental and social pillar and in half of

the examined categories with workforce category excluded, higher in favour of manufac-

turer 2—an SCP preceding manufacturer 1 SCP in the supply chain. Compared with the

score differences between vendor and both manufacturer SCPs, the difference between

the manufacturer SCPs is over ten times smaller. What can be concluded from these ob-

servations is that the existence of green and social bullwhip effect is not affirmed by the

score comparison between the manufacturing SCPs. This observation can be explained to

an extent by the similarity of activities conducted by both manufacturing SCPs—some

sample companies were engaging in component and end product manufacturing simulta-

neously. The case with comparing manufacturing and vendor activities, including whole-

sale and retail, is a drastically different one as a more distinct demarcation can be made

between the activities.

64

8 CONCLUSIONS & DISCUSSION

8.1 Discussion of the results

The objective of this thesis was to explore the effect that SCP and industry have on the

distribution of environmental and social sustainability in manufacturing supply chains.

As a theoretically essential element, the extensions of traditional bullwhip effect, green

and social bullwhip effect, were introduced in this thesis. Much like their “parent phe-

nomenon” bullwhip effect, green and social bullwhip effect are triggered by coercive

pressure exerted by stakeholder group/s on the company governing the supply chain. This

company is oftentimes physically closest to the end consumer, most visible to the stake-

holders. In the case of GBE, coercive pressure materialises into environmental require-

ments. The company governing the supply chain in the downstream relays these require-

ments, more stringent than upon receiving, to the preceding SCP in the supply chain, in

this case to its supplier, to create a safety buffer. The requirements move upstream in the

supply chain becoming more stringent regarding content or implication deadlines of com-

pliance measures. SBE is a parallel phenomenon where, instead of environmental require-

ments, demands for social reforms flow towards upstream and are transformed in the

process.

Klumpp (2011) was among the first in academic literature to study the concept of GBE.

Further investigations on GBE were done most profoundly by Lee et al. (2014) and Seles

et al. (2016). Findings made by Lee et al. (2014) and Seles et al. (2016) support the exist-

ence of GBE. SBE, however, has been scarcely studied in academic literature, rendering

this thesis one of the first academic publications to do so. Environmental and social sus-

tainability issues in supply chains are often conjoined, when sustainability issues are dis-

cussed beyond the environmental realm, as these two phenomena bear comparison with

one another. (Lee 2011; Klassen & Vereecke 2012; Lee et al. 2014; Eriksson & Svensson

2015; Schmidt et al. 2017.) Triple bottom line concept popularised by Elkington in mid-

1990s coupled environmental and social dimensions of business together, at least on a

theoretical level, and was a contributing factor in the convergence of environmental and

social sustainability research (Elkington 1999).

Another concept related to environmental sustainability in supply chains alongside

GBE is supply chain position paradox introduced by Schmidt et al. (2017). According to

this concept, implemented GSCM practices generate the highest yields when imple-

mented the furthest from the end consumer in the upstream of the supply chain and yields

lower as the proximity to end consumer increases. The number of implemented GSCM

practices also peaks at SCP closest to the end consumer. Villena and Gioia (2018) add

65

that lower-tier suppliers in the upstream tend to administer environmental and social sus-

tainability issues passively, presenting the largest and most probable source of environ-

mental and social misconduct in the supply chain. Supporting observations were earlier

made by Plambeck (2012).

The research conducted in this thesis provides partial support to the existence of both

green and social bullwhip effect but did not accomplish to affirm the presence of such

phenomena unequivocally in manufacturing supply chains. In the pioneering studies on

GBE by Lee et al. (2014) and Seles et al. (2016), research conducted was case study with

the division of SCPs consisting, in the case of Lee et al. (2014), of three tiers, OEM, first-

tier supplier and second-tier supplier. In the case study by Seles et al. (2016) four tiers,

i.e. automotive battery manufacturer “Alpha”, Alpha’s customer, (heavy vehicle manu-

facturer), Alpha’s supplier (plastic component supplier) and CETESB (governmental

body), were chosen for examination. In this research, wholesale and retail actors were

merged and introduced as the vendor SCP. A very similar division was used by Schmidt

et al. (2017)—raw material supplier, component supplier, OEM and distributors/retailers.

For this research, ESG data was acquired from 290 European manufacturing compa-

nies diverging in size, industrial activity and nationality. ESG data was refined to include

scores measuring environmental and social sustainability. The sample companies were

assigned an SCP and an industry attribute. SCPs used were manufacturer 1 at the upstream

of the supply chain, extracting basic resources and manufacturing components, manufac-

turer 2, producing end products and vendor SCP, which consists of companies specialised

in wholesale and retail activities. Following Lorentz et al. (2016b), industry categorisation

chosen for this research was as follows: process industry, light industry, metal refining

and metal products, machines, appliances and transport equipment and computers and

electronics. Group means were calculated for each SCP and industry and these means

were then tested with one-way ANOVA tests to discover, if statistically significant dif-

ferences between the group means exist.

Results of the f-tests and Welch’s tests revealed statistically significant differences in

eight out of nine groups when SCP was used as the independent variable and environ-

mental and social sustainability category and pillar scores of ESG data as the dependent

variable. In f- and Welch’s tests, the only category where statistically significant differ-

ences were not present was workforce. In post hoc tests, statistically significant differ-

ences were detected only in the innovation category when manufacturer SCPs were com-

pared. In further post hoc tests between manufacturer and vendor SCPs, only categories,

wherein statistically significant differences were not present between SCPs, were emis-

sions, manufacturer 1 and vendor, and innovation, manufacturer 2 and vendor.

In consonance with green and social bullwhip effect theory, environmental and social

sustainability scores improved when moved upstream in the supply chain—from vendor

to manufacturer 2, the score gap was perceptible. However, environmental and social

66

scores did not increase when moved from end product manufacturing to basic resource

extraction and component manufacturing, in five out of eight comparisons including en-

vironmental and social pillar scores. Score gaps were also not nearly as evident as they

were between vendor and manufacturing SCPs.

The narrow gap between environmental and social sustainability scores of manufac-

turing SCPs can be explained to a certain degree by the similar, and occasionally over-

lapping, industrial activities. The demarcation between manufacturing and wholesale/re-

tail activities is much more distinct than one between manufacturing SCPs. Naturally,

component and end product manufacturing, both being manufacturing activities, have

more common denominators together, are more homogenous and resemble each other

more than manufacturing and sales activities carried out by wholesalers and retailers, but

other factors for the similarity of manufacturer SCPs also exist. Studies by Hingley (2005)

and Bykadorov et al. (2016) argue that retailer SCP oftentimes has considerable negotia-

tion power over the manufacturing SCPs. This may render manufacturers more willing to

horizontally integrate with other manufacturers for enhanced negotiation power. Manu-

facturers are also bound by intrinsically different kind of legislation than retailers, and

manufacturing activities generally are more heavily legislated than retailing activities,

consigning the regulative burden on manufacturers. Manufacturing activities consist of

practices physically transforming a product; in this process, risk of environmental and

social misconduct oftentimes far exceeds similar risk of wholesale and retailing activities.

In manufacturing process, damage can be inflicted on environment and on workforce in

the form of, e.g. hazardous chemicals spill and work safety violations due to inhumane

working conditions in contrast to wholesale and retail activities where accidents may oc-

cur, for example, when controlling the retail inventory using a forklift. (Miller 2017; Vil-

lena & Gioia 2018; European Commission 2018a; 2018b; 2019.)

When industry was chosen as independent variable instead of SCP, and environmental

and social sustainability category and pillar scores of ESG data remained as dependent

variable, no statistically significant differences were detected between group means. Ac-

cording to the results of this research, industry seems to have no significant effect on the

environmental and social sustainability of a supply chain. Contributing factors for no sta-

tistically significant differences existing between group means could be that industry

groups are not homogenous enough but are rather based on somewhat loose division into

five industries. In a similar vein, another perception on the effect of industry on sustain-

ability is the scarcity of previous research on the phenomenon. The lack of existing re-

search might be explained with a possible notion in place in the academic field that no

connection exists between industry and sustainability, rendering efforts to demonstrate

the interdependence between industry and environmental and social sustainability futile.

Results of hypotheses testing are summarised in Table 11.

67

Table 11 Summary of hypotheses testing

Hypothesis Result

H1a: Environmental sustainability distributes between SCPs

according to green bullwhip effect—

statistically significant differences exist between

environmental sustainability scores of SCPs

Supported to

some extent

H1b: Social sustainability distributes between SCPs

according to proposed social bullwhip effect—

statistically significant differences exist between

social sustainability scores of SCPs

Supported to

some extent

H2a: Industry affects environmental sustainability—

statistically significant differences exist between

environmental sustainability scores of different industries

Rejected

H2b: Industry affects social sustainability—

statistically significant differences exist between

social sustainability scores of different industries

Rejected

Results of this research do not either directly support or oppose supply chain position

paradox, observed by Schmidt et al. (2017), This paradox asserts that the closer a com-

pany is to the end consumer, the higher its GSCM practice levels, and simultaneously the

closer the company is to the end consumer in the supply chain, the less performance gains

it experiences from implementing such practices. The lower environmental and social

sustainability scores obtained by vendor SCPs in comparison to the manufacturers in the

upstream, could indicate diminishing GSCM yields closer to the end consumer, but this

cannot not be firmly proclaimed. The results, however, do conflict with observations

made by Villena and Gioia (2018) to some extent: as opposed to claims that upstream

supply chain positions are the largest and most probable source of environmental and

social sustainability misconduct, manufacturer SCPs scored better than the upstream ven-

dor SCP closest to the end consumer. However, the sample of 22 non-European lower-

tier suppliers used by Villena and Gioia (2018) was radically different than the all-Euro-

pean sample used for this research. Lower-tier suppliers, which were relatively unknown

private companies, had their headquarters and factories located in the United States,

China, Taiwan and Mexico apart from one location in Hong Kong. The differences in

environmental and social sustainability cultures between the countries comprising the two

samples, both post-industrial and emerging economies of Villena & Gioia (2018) versus

post-industrial European economies of this research, might explain the conflict between

the results of said two studies.

In comparison to previous prominent research on GBE by Lee et al. (2014) and Seles

et al. (2016), this research was not a case study, thus providing data from a vastly larger

68

number of sample companies enhancing the applicability and generalisation of results.

When compared to research conducted by Schmidt et al. (2017), where data for sample

was obtained through a self-evaluation survey sent to informants representing companies

conducting business in the German-speaking world, data for this research was collected

by professional analysts specialising in ESG data refinement.

8.2 Managerial implications

The results of this research have provided additional proof to the notion that environmen-

tal and social sustainability do improve when moved from the retail and wholesale activ-

ities in the downstream towards the manufacturers in the upstream of the supply chain.

However, among the manufacturers, improvement is not as radical as when transition is

made from the retail and wholesale activities to manufacturing activities. Scope of SCPs

or tiers in this research was limited to three and all sample companies were European,

meaning that this research did not reach lower-tier suppliers far in the upstream. The sup-

pliers furthest in the upstream are, in the globalised economy, usually located beyond

European borders, on other continents in emerging economies. Suppliers furthest in the

upstream seem to face the most stringent environmental and social requirements as man-

agers at each preceding SCP aim to create a safety buffer for their own operations. This

safety buffer is created by tightening the implementation schedules for compliance

measures or by tightening the content of requirements in anticipation of future, more

stringent regulation or stakeholder pressure to operate even more sustainably. (Lee et al.

2014; Seles et al. 2016; Villena & Gioia 2018.)

The situation for suppliers, due to GBE, is dependent on their strategic importance to

customer company, usually a company governing the supply chain, located in the down-

stream. Lee et al. (2014) observe four different responses taken by managers of customer

companies towards their suppliers in terms of environmental requirements: replace, ne-

gotiate, accommodate or collaborate. Suppliers displaying little strategic importance,

mostly offering commodities, parts which could be fairly eaisly substituted or duplicated

and components in ample supply, were replaced, if they did not meet the requirements

imposed or refused to implement the changes required. These suppliers face the most

stringent requirements and thus the biggest pressure. Suppliers possessing more negotia-

tion power than ones confronted with the replace response were either negotiated with or

accommodation of requirements occurred. The level of stringency in environmental re-

quirements was alleviated when sustainability progress was assured to continue in oper-

ations of supplier. Customer companies using the accommodation response did not pos-

sess enough negotiation power over suppliers and had to make concessions with more

critical suppliers. Collaboration response was reserved for most critical suppliers. This

69

response translates into active involvement in developing supplier capabilities through

monetary investments and intense exchange of technological expertise and information.

(Lee et al. 2014.) The results of this thesis from ANOVA tests, f- and Welch’s tests, point

to an analogous situation in the case of the SBE—requirements for social reforms are

more stringent the further the observed SCP is in the upstream.

Ultimately green and social bullwhip effect raise awareness in supply chains about

sustainability, accelerate the implementation of GSCM practices and social reforms, but

nonetheless expose suppliers furthest in the upstream of the supply chain to most stringent

environmental and social requirements in the whole chain. This may either lead to re-

placement of a supplier or to negotiations or collaboration with a supplier. In the case of

collaboration, supplier may receive monetary support in form of investments in e.g. train-

ing of the personnel, modernisation of production facilities and technological support

through sharing of information and expertise. Seles et al. (2016) propose co-operation

between SCPs as a method to mitigate difficulties in responding to environmental pres-

sure. In a similar vein, Manetti and Toccafondi (2012) and Gualandris et al. (2015) high-

light the importance of certain stakeholders in implementing GSCM practices throughout

the supply chain. Some stakeholders possess certain expertise which can help in the for-

mation of more considerate sustainability objectives, adding incentive for co-operation.

The results of this thesis are somewhat in contradiction with results of study by Villena

and Gioia (2018). Villena and Gioia (2018) claim that sustainability misconduct is most

probable to occur in far upstream of the supply chain, whereas results of this thesis imply

that least sustainable links in the supply chain are wholesalers and retailers in the down-

stream. Regulatory stakeholders should, thus, reconsider the regulation of wholesale and

retail activities in contrast to the heavy legislative burden laid currently on manufacturers,

albeit manufacturing activities can be riskier from an environmental and social point of

view. In other words, stakeholders should turn their attention to activities occurring at the

very downstream of a supply chain. It should, however, be noted that the scope of research

conducted in this thesis is limited to large European-based firms and hence the lower-tier

suppliers were not investigated. GBE or SBE is oftentimes triggered by stakeholders in-

fluencing the company governing the supply chain in the downstream. However, a ques-

tion could be posed that does the practice of stakeholders skipping wholesale/retail tier

preceding the governing company in the supply chain, i.e. exempting wholesalers and

retailers from pressure, aid in rendering supply chains more sustainable? This, coupled

with results of this thesis, would imply that in the current reality, wholesale and retail

activities are, as perceived by stakeholders, effectively excluded from the scrutiny con-

cerning sustainability in favour of companies governing supply chains.

70

8.3 Limitations and future research

Much like with previous studies, notable examples being Lee et al. (2014) and Seles et

al. (2016), the most profound limitation of this research was the limited number of SCPs

or tiers in supply chains observed. Due to the limited number of suitable sample compa-

nies, wholesale and retail SCPs had to be merged into single vendor SCP. The division of

sample companies between two manufacturing SCPs was also an arduous task, as many

companies performed activities which had major characteristics belonging to both manu-

facturing SCPs. Similar issue occurred in case study by Wilhelm et al. (2016) as the dis-

tinction between the first- and second-tier suppliers of a tea production supply chain be-

came blurred due to overlapping activities of suppliers. The differences in used samples

between the original GBE studies by Lee et al. (2014) and Seles et al. (2016) and this

research mentioned must be pointed out, as well. Previous two studies delved in individ-

ual supply chains consisting, in the case of Lee et al. (2014), of second-tier and first-tier

suppliers and OEMs, and in the case of Seles et al. (2016), of automotive battery manu-

facturer, its customer, the supplier of a battery manufacturer, and a governmental body.

The sample of this research, however, included wholesale and retail activities as well,

much like the study by Schmidt et al. (2017). This extension of supply chain tiers to

wholesale and retail activities must be taken into consideration when comparing the re-

sults of this research on GBE and SBE as the approach was different than one taken by

Lee et al. (2014) and Seles et al. (2016).

The somewhat artificial split between two manufacturer SCPs may have been a con-

tributing factor to why the results did not unequivocally support the existence of green

and social bullwhip effect at the upstream of manufacturing supply chains. Thus, increase

in the number of examined SCPs/tiers would generate more accurate information as the

division of value-creating activities would not overlap as much as they did with the three-

fold model used in this research. According to Plambeck (2012) and Villena and Gioia

(2018), the greatest risk of environmental or social misconduct lies furthest in the up-

stream—lower-tier suppliers. Villena and Gioia (2018) assert that passiveness demon-

strated by lower-tier suppliers is caused by a smaller risk of punishment or penalisation

in the upstream, where actors are largely hidden from the direct pressure of stakeholders.

The sample used in this research did not reach all the way to the upstream as aggre-

gated and precise data collection from lower-tier suppliers is problematic. In addition to

the increase in the number of SCPs in the supply chain for more accurate examination,

the division of sample companies to industries could have been more even. Industry with

the smallest sample size, metal refining and metal products, consisted only of 16 compa-

nies, whereas the largest industry sample size, 113 companies, was that of process indus-

try. Larger sample sizes, or more even ones, could have improved the representativity of

71

the sample. For future research, increase in the number of SCPs/tiers and sample sizes of

industries would be desirable.

A criticism towards the data itself is the source—Thomson Reuters’s ESG scoring

process, on the measure level, is not very transparent. This lack of transparency prevents

the assessment of reliability and objectivity of the scoring process, thus forcing the data

to be used as given. The inclusion of controversies scores, which magnify the negative

effect of any larger media backlash, would not have most likely altered the results in any

dramatic way. Controversies scores were omitted when determining the environmental

and social sustainability of sample companies due to the complexity of commensurability

of environmental and social pillars with controversies score and low transparency of the

scoring process. However, ESG data by Thomson Reuters has been used also in previous

studies by, e.g. Chang et al. (2014), Sassen et al. (2016) and Garcia et al. (2017).

For future research, involvement of further tiers of upstream suppliers, similarly to

Seles et al. (2016), is proposed to formulate a more holistic image and understand envi-

ronmental and social sustainability distribution in supply chains better. Especially lower-

tier suppliers residing in the very upstream of supply chains should be thoroughly exam-

ined. In order to truly target the companies possessing the strongest negotiation power

and, hence ones governing the supply chains and the most potential to trigger green and

bullwhip effect, large end product manufacturers as well as companies governing the sup-

ply chain should be further studied, as well. (Schmidt et al 2017.) Companies like Apple

and Nestlé govern their own supply chains and as sustainability violations surface, con-

sumers and stakeholder groups tend to target the largest, most visible companies rather

than decide to boycott certain retailers, much smaller in terms of revenue and market

capitalisation (Schmidt et al. 2017; Touryalai & Stoller 2018; Ethical Consumer 2019).

However, if enough retailers start to boycott large end product manufacturers, this even-

tually has an impact on manufacturing companies, as well.

Another facet for future research would be to investigate the social dimension of bull-

whip effect and social sustainability issues in supply chains further as the research field

has been incontrovertibly dominated by exploration of environmental issues and green

considerations in supply chains.

72

REFERENCES

Adams, J. – Bosselmann, K. – Cartwright, W. – Davis, P. – Hertnon, S. – Howell, R. –

Lawton, M. – Peet, J. – Reid, W. – Salinger, J. – Trerise, K. – Verity, R.

(2009) Strong sustainability for New Zealand: Principles and scenarios.

SANZ Report, Nakedize Ltd., Auckland.

Adams, William M. (2006) The Future of Sustainability: Re-thinking Environment and

Development in the Twenty-first Century. The IUCN Renowed Thinkers

Meetings, 29–31.

Ambec, S. – Lanoie, P. (2008) Does it pay to be green? A systematic overview. Academy

of Management Perspectives, Vol. 22 (4), 45–62.

Aragón-Correa, J. A. – Sharma, S. (2003) A contingent resource-based view of proactive

corporate environmental strategy. Academy of Management Review, Vol. 28

(1), 71–88.

Arbnor, I. – Bjerke, B. (1997) Methodology for Creating Business Knowledge. SAGE

Publications. Thousand Oaks, California.

Asgary, N. – Li, G. (2016) Corporate Social Responsibility: Its Economic Impact and

Link to the Bullwhip Effect. Journal of Business Ethics, Vol. 135 (4), 665–

681.

Ateş, M. A. – Bloemhof, J. – Van Raaij, E. M. – Wynstra, F. (2012) Proactive environ-

mental strategy in a supply chain context: the mediating role of investments.

International Journal of Production Research. Vol. 50 (4), 1079–1095.

Auger, P. – Burke, P. F. – Devinney, T. M. – Louviere, J. J. (2003) What will consumers

pay for social product features? Journal of Business Ethics, Vol. 42 (3),

281–304.

Balasubramanian, P. – Soman, S. (2018) Awareness regarding fair trade concept and the

factors influencing the fair trade apparel buying behaviour of consumers in

Cochin City. Journal of Strategic Marketing, 30 May 2018, 1–18.

Bansal, P. – Song, H.-C. (2017) Similar But Not the Same: Differentiating Corporate

Sustainability from Corporate Responsibility. Academy of Management An-

nals, Vol. 11 (1), 105–149.

Barbiroli, G. – Raggi, A. (2003) A method for evaluating the overall technical and eco-

nomic performance of environmental innovations in production cycles.

Journal of Cleaner Production, Vol. 11 (4), 365–374.

Berry, H., – McEachern, M. G. (2005) Informing ethical consumers. In: The ethical con-

sumer, eds. Rob Harrison – Deirdre Shaw – Terry Newholm, 69–87. Sage

Publications, London.

Beske, P. – Land, A. – Seuring, S. (2014) Sustainable supply chain management practices

and dynamic capabilities in the food industry: A critical analysis of the lit-

erature. International Journal of Production Economics, Vol. 152, 131–143.

73

Bezençon, V. – Blili, S. (2010) Ethical products and consumer involvement: what’s new?

European Journal of Marketing, Vol. 44 (9/10), 1305–1321.

Blankstein, A. – Kaplan, A. (2019) California jury hits Monsanto with $2 billion judg-

ment in cancer lawsuit. <https://www.nbcnews.com/politics/justice-depart-

ment/california-jury-hits-monsanto-2-billion-judgment-cancer-lawsuit-

n1005191>, retrieved 14.5.2019.

Bonini, S. – Oppenheim, J. (2008) Cultivating the green consumer. Stanford Social Inno-

vation Review, Vol. 6 (4), 56–61.

Bray, J. – Johns, N. – Kilburn, D. (2011) An exploratory study into the factors impeding

ethical consumption. Journal of Business Ethics, Vol. 98 (4), 597–608.

Burke, P. F. – Eckert, C. – Davis, S. (2014) Segmenting consumers’ reasons for and

against ethical consumption. European Journal of Marketing, Vol. 48

(11/12), 2237–2261.

Bursztyn, M. – Drummond, J. (2014) Sustainability science and the university: pitfalls

and bridges to interdisciplinarity. Environmental Education Research, Vol.

20 (3), 313–332.

Busch, T. – Hoffmann, V. H. (2011) How hot is your bottom line? Linking carbon and

financial performance. Business and Society, Vol. 50 (2), 233–265.

Buysse, K. – Verbeke, A. (2003) Proactive Environmental Strategies: A Stakeholder

Management Perspective. Strategic Management Journal, Vol. 24 (5), 453–

470.

Bykadorov, I. – Ellero, A. – Funari, S. – Kokovin, S. – Pudova, M. (2016) Chain Store

Against Manufacturers: Regulation Can Mitigate Market Distortion. In:

Discrete Optimization and Operations Research. DOOR 2016. Lecture

Notes in Computer Science, eds. Kochetov, Yury – Khachay, Michael –

Beresnev, Vladimir – Nurminski, Evgeni – Pardalos, Panos, Vol. 9869.

Springer, Cham.

Caniato, F. – Caridi, M. – Crippa, L. – Moretto, A. (2012) Environmental sustainability

in fashion supply chains: An exploratory case based research. International

Journal of Production Economics, Vol. 135, 659–670.

Cannella, S. – Dominguez, R. – Framinan, J. M. – Ponte, B. (2018) Evolving Trends in

Supply Chain Management: Complexity, New Technologies, and Innova-

tive Methodological Approaches. Complexity, Vol. 2018, Article ID

7916849, 1–3.

Cardoso, T. F. – Watanabe, M. D. B. – Souza, A. – Chagas, M. F. – Cavalett, O. – Morais,

E. R. – Nogueira, L. A. H. – Leal, M. R. L. V. – Braunbeck, O. A. – Cortez,

L. A. B. – Bonomi, A. (2019) A regional approach to determine economic,

environmental and social impacts of different sugarcane production systems

in Brazil. Biomass and Bioenergy, Vol. 120, 9–20.

Carter, C. R. – Jennings, M. M. (2002) Logistics social responsibility: an integrative

framework. Journal of Business Logistics, Vol. 23 (1). 145–180.

74

Carter, C. R. – Rogers, D. S. (2008) A framework of sustainable supply chain manage-

ment: moving toward new theory. International Journal of Physical Distri-

bution & Logistics Management, Vol. 38 (5), 360–387.

Cato, Molly S. (2008) Green Economics: An Introduction to Theory, Policy and Practice.

1st edition. Routledge, London.

Central Compilation & Translation Press (2016) The 13th Five-Year Plan For Economic

and Social Development of The People’s Republic of China (2016–2020).

<en.ndrc.gov.cn/policyrelease/201612/P020161207645766966662.pdf>,

retrieved 22.2.2019.

Chen, X. – Wang, X. (2016) Effects of carbon emission reduction policies on transporta-

tion mode selections with stochastic demand. Transportation Research Part

E, Vol. 90, 196–205.

Cheng, B. – Iannou, I. – Serafeim, G. (2014) Corporate social responsibility and access

to finance. Strategic Management Journal, Vol. 35 (1), 1–23.

Chenhall, Robert H. (2005) Integrative strategic performance measurement systems, stra-

tegic alignment of manufacturing, learning and strategic outcomes: an ex-

ploratory study. Accounting, Organizations and Society, Vol. 30 (5), 395–

422.

Chiu, S.-C. – Sharfman, M. (2011) Legitimacy, Visibility, and the Antecedents of Cor-

porate Social Performance: An Investigation of the Instrumental Perspec-

tive. Journal of Management, Vol. 37 (6), 1558–1585.

Christian Aid (2004) Behind the mask: The real face of corporate social responsibility.

London: Christian Aid.

Darnall, N. – Edwards, D., jr. (2006) Predicting the cost of environmental management

system adoption: The role of capabilities, resources and ownership struc-

ture. Strategic Management Journal, Vol. 27 (4), 301–320.

Das, C. – Jharkharia, S. (2018) Low carbon supply chain: a state-of-the-art literature re-

view. Journal of Manufacturing Technology Management, Vol. 29 (2), 398–

428.

Delmas, M. – Montiel, I. (2009) Greening the Supply Chain: When Is Customer Pressure

Effective? Journal of Economics & Management Strategy, Vol. 18 (1), 171–

201.

DiMaggio, P. J. – Powell, W. W. (1983) The Iron Cage Revisited: Institutional Isomor-

phism and Collective Rationality in Organizational Fields. American Soci-

ological Review, Vol. 48 (2), 147–160.

Dizikes, Peter (2013) The Beer Game. MIT News 22.10.2013. <https://www.technolo-

gyreview.com/s/520181/the-beer-game/>, retrieved 4.11.2018.

Dodd-Frank Wall Street Reform and Consumer Protection Act (2010), Pub. L. 111-203,

124 Stat 1376-2223, 12 U.S.C. §1502.

75

dormakaba (2018) Products. <https://www.dormakaba.com/en/products>, retrieved

3.11.2018.

Dossi, A. – Patelli, L. (2010) You Learn From What You Measure: Financial and Non-

financial Performance Measures in Multinational Companies. Long Range

Planning, Vol. 43 (4), 498–526.

Duhigg, C. – Barboza, D. (2012) In China, Human Costs Are Built Into an iPad. The New

York Times 25.1.2012. <https://www.nytimes.com/2012/01/26/business/ie-

conomy-apples-ipad-and-the-human-costs-for-workers-in-china.html>, re-

trieved 11.4.2019.

Du Plessis, J. – Bam, W. (2018) Comparing the Sustainable Development Potential of

Industries: A Role for Sustainability Disclosures? Sustainability, Vol. 10

(3), 1–30.

Elkington, John (1999) Cannibals with Forks: The Triple Bottom Line of 21st Century

Business. Capstone Publishing Limited, Oxford.

Elkington, John (2004) Enter the Triple Bottom Line. In: The Triple Bottom Line, does it

all add up?: Assessing the Sustainability of Business and CSR, eds. Hen-

riques, Adrian – Richardson, Julie, 1–16. Earthscan, London.

Elkington, John (2018) 25 Years Ago I Coined the Phrase “Triple Bottom Line.” Here’s

Why It’s Time to Rethink It. Harvard Business Review 25.6.2018.

<https://hbr.org/2018/06/25-years-ago-i-coined-the-phrase-triple-bottom-

line-heres-why-im-giving-up-on-it>, retrieved 3.10.2018.

Ellen MacArthur Foundation (2019) What is a circular economy? <https://www.el-

lenmacarthurfoundation.org/circular-economy/concept>, retrieved

21.2.2019.

Eriksson, D. – Svensson, G. (2015) Elements affecting social responsibility in supply

chains. Supply Chain Management: An International Journal, Vol. 20 (5),

561–566.

Ethical Consumer (2012) Ethical Consumer Markets Report 2012. <https://www.ethical-

consumer.org/sites/default/files/inline-files/ethical-consumer-markets-re-

port-2012.pdf >, retrieved 23.3.2019.

Ethical Consumer (2018) Ethical Consumer Markets Report 2018. <https://www.ethical-

consumer.org/sites/default/files/inline-files/EC%20Markets%20Re-

port%202018%20FINAL.pdf>, retrieved 23.3.2019.

Ethical Consumer (2019) Boycotts List. <https://www.ethicalconsumer.org/ethicalcam-

paigns/boycotts>, retrieved 29.1.2019.

European Commission (2018a) New waste rules will make EU global front-runner in

waste management and recycling. <https://ec.europa.eu/info/news/new-

waste-rules-will-make-eu-global-front-runner-waste-management-and-re-

cycling-2018-apr-18_en>, retrieved 15.5.2019.

76

European Commission (2018b) Public consultation on “retail regulations in a multi-

channel environment” synopsis report accompanying the document Com-

munication from the Commission to the European Parliament, the Council,

the European Economic and Social Committee and the Committee of the

Regions on a European retail sector fit for the 21st century. <https://eur-

lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52018SC0237>, re-

trieved 15.5.2019.

European Commission (2019) CE marking; manufacturers. <https://ec.eu-

ropa.eu/growth/single-market/ce-marking/manufacturers_en>, retrieved

15.5.2019.

Field, Andy (2018) Discovering statistics using IBM SPSS Statistics: and sex and drugs

and rock ‘n’ roll. 5th edition. SAGE, London.

Figge, F. – Hahn, T. – Schaltegger, S. – Wagner, M. (2002) The Sustainability Balanced

Scorecard – linking sustainability management to business strategy. Busi-

ness Strategy & the Environment, Vol. 11 (5), 269–284.

Forrester, Jay W. (1961) Industrial Dynamics. MIT Press: Cambridge, Massachusetts.

Fowler, S. J. – Hope, C. (2007) A critical review of sustainable business indices and their

impact. Journal of Business Ethics, Vol. 76 (3), 243–252.

Friede, G. – Busch, T. – Bassen, A. (2015) ESG and financial performance: aggregated

evidence from more than 2000 empirical studies. Journal of Sustainable Fi-

nance & Investment, Vol. 5 (4), 210–233.

FTSE Russell (2018) Current to new ICB Structural Conversion Map Detail.

<https://www.ftserussell.com/files/support-documents/icb-structural-con-

version-map-detail>, retrieved 25.8.2018.

Fullerton, Jamie (2018) Suicide at Chinese iPhone factory reignites concern over working

conditions. The Telegraph 7.1.2018. <https://www.tele-

graph.co.uk/news/2018/01/07/suicide-chinese-iphone-factory-reignites-

concern-working-conditions/>, retrieved 23.8.2018.

Garcia, A. S. – Mendes-Da-Silva, W. – Orsato, R. J. (2017) Sensitive industries produce

better ESG performance: Evidence from emerging markets. Journal of

Cleaner Production, Vol. 150, 135–147.

Gaurav, N. – Sivasankari, S. – Kiran, G. S. –Ninawe, A. – Selvin, J. – Utilization of

bioresources for sustainable biofuels: A Review. Renewable and Sustaina-

ble Energy Reviews, Vol. 73, 205–214.

GEMI (2019) About us. <http://gemi.org/about-us/>, retrieved 9.3.2019.

Genovese, A. – Acquaye, A. A. – Figueroa, A. – Koh, S. C. L. (2017) Sustainable supply

chain management and the transition towards a circular economy: Evidence

and some applications. Omega, Vol. 66, 344–357.

George, D. – Mallery, M (2010) SPSS for Windows Step by Step: A Simple Guide and

Reference, 17.0 update. 10th edition. Pearson, Boston.

77

Global Witness (2014) Tackling Conflict Minerals: How a Chinese Initiative Can Ad-

dress Chinse Companies’ Risks. Global Witness, October 2014, London.

Gray, Rob (2006) Does sustainability reporting improve corporate behaviour?: Wrong

question? Right time? Accounting and Business Research, International Ac-

counting Policy Forum, 65–88.

Green, K. – Morton, B. – New, S. (2000) Greening organizations. Organization & Envi-

ronment, Vol. 13 (2), 206–225.

GRI (2018) About GRI. <https://www.globalreporting.org/Information/about-

gri/Pages/default.aspx>, retrieved 4.10.2018.

Grimm, J. H. – Hofstetter, J. S. – Sarkis, J. (2014) Critical factors for sub-supplier man-

agement: A sustainable food supply chains perspective. International Jour-

nal of Production Economics, Vol. 152, 159–173.

Gualandris, J. – Klassen, R. D. – Vachon, S. – Kalchschmidt, M. (2015) Sustainable eval-

uation and verification in supply chains: Aligning and leveraging accounta-

bility to stakeholders. Journal of Operations Management, Vol. 38, 1–13.

Hair, J. F. – Black, W. C. – Babin, B. J. – Anderson, R. E. (2010) Multivariate Data

Analysis: A Global Perspective. 7th edition. Pearson Education, Upper Sad-

dle River, New Jersey.

Hancock, Alice (2017) Younger consumer drive shift to ethical products. Financial Times

22.12.2017. <https://www.ft.com/content/8b08bf4c-e5a0-11e7-8b99-

0191e45377ec>, retrieved 23.8.2018.

Harris, Paul (2012) Apple hit by boycott call over worker abuses in China. The Guardian

29.1.2012. <https://www.theguardian.com/technology/2012/jan/29/apple-

faces-boycott-worker-abuses>, retrieved 11.4.2019.

Hart, S. L. – Ahuja, G. (1996) Does it pay to be green? An empirical examination of the

relationship between emission reduction and firm performance. Business

Strategy and the Environment, Vol. 5 (1), 30–37.

Hartmann, J. – Moeller, S. (2014) Chain liability in multitier supply chains? Responsibil-

ity attributions for unsustainable supplier behavior. Journal of Operations

Management, Vol. 32, 281–294.

Henderson, Hazel (1991) Paradigms in Progress: Life Beyond Economics. 1st edition.

Knowledge Systems Inc., Indianapolis.

Herring, S. C. – Christidis, N. – Hoell, A. – Kossin, J. P. – Schreck, C. J. III – Stott, P. A.

(2018) Explaining extreme events of 2016 from a climate perspective. Bul-

letin of the American Meteorological Society, Vol. 99 (1), 51–53.

Hingley, Martin K. (2005) Power to all our friends? Living with imbalance in supplier–

retailer relationships. Industrial Marketing Management, Vol. 34 (8), 848–

858.

78

Hofmann, H. – Schleper, M. C. – Blome, C. (2018) Conflict Minerals and Supply Chain

Due Diligence: An Exploratory Study of Multi-tier Supply Chains. Journal

of Business Ethics, Vol. 147 (1), 115–141.

Hu, Z. – Rao, C. – Zheng, Y. – Huang, D. (2015) Optimization Decision of Supplier

Selection in Green Procurement under the Mode of Low Carbon Economy.

International Journal of Computational Intelligence Systems, Vol. 8 (3),

407–421.

Investopedia (2019) Ratio Analysis. <https://www.investopedia.com/terms/r/ratioanaly-

sis.asp>, retrieved 22.2.2019.

IPCC (2018) Summary for Policymakers of IPCC Special Report on Global Warming

of 1.5°C approved by governments.

<https://www.ipcc.ch/news_and_events/pr_181008_P48_spm.shtml>, re-

trieved 4.11.2018.

Izadikhah, M. – Farzipoor Saen, R. (2016) Evaluating sustainability of supply chains by

two-stage range directional measure in the presence of negative data. Trans-

portation Research Part D: Transport and Environment, Vol. 49, 110–126.

Jabbour, C. J. C. – Neto, A. S. – Gobbo, J. A., jr. – De Souza Ribeiro, M. – Lopes de

Sousa Jabbour, A. B. (2015) Eco-innovations in more sustainable supply

chains for a low-carbon economy: A multiple case study of human critical

success factors in Brazilian leading companies. International Journal of

Production Economics, Vol. 164, 245–257.

Kang, J.-W. – Namkung, Y. (2018) The Effect of Corporate Social Responsibility on

Brand Equity and the Moderating Role of Ethical Consumerism: The Case

of Starbucks. Journal of Hospitability & Tourism Research, Vol 42 (7),

1130–1151.

Kaplan, R. S. – Norton D. P. (1993) Putting the Balanced Scorecard to Work. Harvard

Business Review September-October 1993 issue.

<https://hbr.org/1993/09/putting-the-balanced-scorecard-to-work>, re-

trieved 5.3.2019.

Kasanen, E. – Lukka, K. – Siitonen, A. (1993) The constructive approach in management

accounting research. Journal of Management Accounting Research, Vol. 5,

243–264.

Klassen, R. – Vereecke, A. (2012) Social issues in supply chains: Capabilities link re-

sponsibility, risk (opportunity), and performance. International Journal of

Production Economics, Vol. 140, 103–115.

Klumpp, Matthias (2011) Green Bullwhip Effect Simulation Concept. In: The 2011 Eu-

ropean Simulation and Modelling Conference, Proceedings October 24-26,

2011 at University of Mino, Guimaraes, Portugal, eds. P. Navais – J. Ma-

chado – C. Analide – A. Abelha, 263–265. Conference Proceedings October

24-26, 2011 at University of Mino, Guimaraes, Portugal.

79

Klumpp, M. – Toklu, N. E. – Papapanagiotou, V. – Montemanni, R. – Gambardella, L.

M. (2016) Green Bullwhip Effect Cost Simulation in Distribution Networks.

In: Dynamics in Logistics - Proceedings of the 4th International Conference

LDIC, 2014 Bremen, Germany, eds. Herbert Kotzab – Jürgen Pannek –

Klaus-Dieter Thoben, 387–395. Springer, Cham.

Klumpp, Matthias (2019) Green Bullwhip Effect Revisited: How Sustainable Lifestyles

Might Influence Supply Chains: Interdependencies, Transformation Strate-

gies and Decision Making. In: Innovative Logistics Services and Sustainable

Lifestyles, eds. Ani Melkonyan – Klaus Krumme, 105–114. Springer, Cham.

Krause, D. R. – Handfield, R. B. – Tyler, B. B. (2007) The relationships between supplier

development, commitment, social capital accumulation and performance

improvement. Journal of Operations Management, Vol. 25 (2), 528–545.

Kuo, R. J. – Hsu, C. W. – Chen, Y. L. (2015) Integration of fuzzy ANP and fuzzy TOPSIS

for evaluating carbon performance of suppliers. International Journal of En-

vironmental Science and Technology, Vol. 12 (12), 3863–3876.

Laari, S. – Töyli, J. – Solakivi, T. – Ojala, L. (2016) Firm performance and customer-

driven green supply chain management. Journal of Cleaner Production,

Vol. 112, 1960–1970.

Laari, S. – Töyli, J. – Ojala, L. (2017) Supply chain perspective on competitive strategies

and green supply chain management strategies. Journal of Cleaner Produc-

tion, Vol. 141, 1303–1315.

Lane, D. C. – Sterman, J. D. (2011) Jay Forrester: Chapter 20. In: Profiles in Operations

Research: Pioneers and Innovators, eds. Arjang A. Assad – Saul. I. Gass,

363–386. New York, Springer.

Lee, H. L. – Padmanabhan, V. – Whang, S. (1997a) Information distortion in a supply

chain: The bullwhip effect. Management Science, Vol. 43 (4), 546–558.

Lee, H. L. – Padmanabhan, V. – Whang, S. (1997b) The Bullwhip Effect in Supply

Chains. MIT Sloan Management Review, Vol. 38 (3), 93–102.

Lee, K.-H. – Cin, B.-C. – Lee, E.-Y. (2016) Environmental Responsibility and Firm Per-

formance: The Application of an Environmental, Social and Governance

Model. Business Strategy and the Environment, Vol. 25 (1), 40–53.

Lee, Min-Dong P. (2011) Configuration of External Influences: The Combined Effects

of Institutions and Stakeholders on Corporate Social Responsibility Strate-

gies. Journal of Business Ethics, Vol. 102 (2), 281–298.

Lee, S.-Y. – Klassen, R. D. – Furlan, A. – Vinelli, A. (2014) The green bullwhip effect:

Transferring environmental requirements along a supply chain. Interna-

tional Journal of Production Economics, Vol. 156, 39–51.

Levin, S. – Greenfield, P. (2018) Monsanto ordered to pay $289m as jury rules weedkiller

caused man's cancer. The Guardian 11.8.2018. <https://www.theguard-

ian.com/business/2018/aug/10/monsanto-trial-cancer-dewayne-johnson-

ruling>, retrieved 20.2.2019.

80

LG (2013) Conflict minerals. <https://www.lg.com/global/sustainability/business-part-

ner/conflict-minerals>, retrieved 3.11.2018.

Lo, Sonia M. (2013) Effects of supply chain position on the motivation and practices of

firms going green. International Journal of Operations & Production Man-

agement, Vol. 34 (1), 93–114.

Lorentz, H. – Solakivi, T. – Töyli, J. – Ojala, L. (2016a) Trade credit dynamics during

the phases of the business cycle – a value chain perspective. Supply Chain

Management: An International Journal, Vol. 21 (3), 363–380.

Lorentz, H. – Hilmola, O.-P. – Malmsten, J. – Srai, J. S. (2016b) Cluster analysis appli-

cation for understanding SME manufacturing strategies. Expert Systems

With Applications, Vol. 66, 176–188.

Low, Chris (2006) A framework for the governance of social enterprise. International

Journal of Social Economics, Vol. 33 (5/6), 376–385.

MacDonald, C. – Norman, W. (2007) Rescuing the baby from the triple-bottom-line bath-

water: A reply to Pava. Business Ethics Quarterly, Vol. 17 (1), 111–114.

Mal, S. – Singh, R. B. – Huggel, C. – Grover A. (2017) Introducing Linkages Between

Climate Change, Extreme Events, and Disaster Risk Reduction. In: Climate

Change, Extreme Events and Disaster Risk Reduction. Sustainable Devel-

opment Goals Series, eds. Suraj Mal – R. B. Singh – Christian Huggel, 1–

14. Springer, Cham.

Manetti, G. – Toccafondi, S. (2012) The Role of Stakeholders in Sustainability Reporting

Assurance. Journal of Business Ethics, Vol. 107 (3), 363–377.

Mani, V. – Agrawal, R. – Sharma, V. (2015) Supply Chain Social Sustainability: A Com-

parative Case Analysis in Indian Manufacturing Industries. Procedia - So-

cial and Behavioral Sciences, Vol. 189, 243–251.

Meixell, M. J. – Luoma, P. (2015) Stakeholder pressure in sustainable supply chain man-

agement: A systematic review. International Journal of Physical Distribu-

tion and Logistics Management, Vol. 45, 69–89.

Millar, R. – Hall, K. (2013) Social Return on Investment (SROI) and Performance Meas-

urement. Public Management Review, Vol 15 (6), 923–941.

Miller, Julie (2017) Retailers and producers tussle over Prop 65 obligations.

<https://chemicalwatch.com/57317/retailers-and-producers-tussle-over-

prop-65-obligations>, retrieved 15.5.2019.

Milman, A. – Short, A. (2008) Incorporating resilience into sustainability indicators: An

example for the urban water sector. Global Environmental Change, Vol. 18

(4), 758–767.

Milne, M. J. – Gray, R. (2013) W(h)ither Ecology? The Triple Bottom Line, the Global

Reporting Initiative, and Corporate Sustainability Reporting. Journal of

Business Ethics, Vol. 118, 13–29.

81

Mittelstaedt, J. D. – Shultz, C. J. – Kilbourne, W. E. – Peterson, M. (2014) Sustainability

as Megatrend: Two Schools of Macromarketing Thought. Journal of Mac-

romarketing, Vol. 34 (3), 253–264.

Moldavska, A. – Welo, T. (2017) The concept of sustainable manufacturing and its defi-

nitions: A content-analysis based literature review. Journal of Cleaner Pro-

duction, Vol. 166, 744–755.

Montabon, F. – Pagell, M. – Wu, Z. (2016) Making Sustainability Sustainable. Journal

of Supply Chain Management, Vol. 52 (2), 11–27.

MSCI (2019) MSCI ESG Ratings Methodology. <https://www.msci.com/docu-

ments/10199/123a2b2b-1395-4aa2-a121-ea14de6d708a>, retrieved

10.3.2019.

Mulia, P. – Behura, A. K. – Kar, S. (2016) Categorical Imperative in Defense of Strong

Sustainability. Problemy Ekorozwoju – Problems of Sustainable Develop-

ment, Vol. 11 (2), 29–36.

Murphy, Hannah (2018) Bloomberg and Reuters lose data share to smaller rivals. Finan-

cial Times 21.3.2018. <https://www.ft.com/content/622855dc-2d31-11e8-

9b4b-bc4b9f08f381>, retrieved 9.1.2019.

Murray, A. – Skene, K. – Haynes, K. (2017) The Circular Economy: An Interdisciplinary

Exploration of the Concept and Application in a Global Context. Journal of

Business Ethics, Vol. 140 (3), 369–380.

Neilimo, K. – Näsi, J. (1980) Nomoteettinen tutkimusote ja Suomalainen yrityksentalous-

tiede, tutkimus positivismin soveltamisesta. Tampereen yliopiston. Yri-

tyksen taloustieteen ja yksityisoikeuden laitoksen julkaisuja A2:12.

Nielsen (2013) 50 per cent of global consumers surveyed willing to pay more for goods,

services from socially responsible companies, up from 2011. <www.niel-

sen.com/us/en/press-room/2013/nielsen-50-percent-of-global-consumers-

surveyed-willing-to-pay-more-fo.html#sthash.996N9DhT.dpuf>, retrieved

23.3.2019.

Norman, W. – MacDonald, C. (2004) Getting to the Bottom of "Triple Bottom Line".

Business Ethics Quarterly, Vol. 14 (2), 243–262.

Pagell, M. – Shevchenko, A. (2014) Why Research in Sustainable Supply Chain Man-

agement Should Have no Future. Journal of Supply Chain Management,

Vol. 50 (1), 44–55.

Papaoikonomou, E. – Valverde, M. – Ryan, G. (2012) Articulating the meanings of col-

lective experiences of ethical consumption. Journal of Business Ethics, Vol.

110 (1), 15–32.

Pattison, Pete (2018) Samsung should try imagining a world where big firms respect

workers. The Guardian 8.11.2018. <https://www.theguardian.com/global-

development/2018/nov/08/samsung-should-try-imagining-a-world-where-

big-firms-respect-workers>, retrieved 12.4.2019.

82

Payman, A. – Searcy, C. (2013) A comparative literature analysis of definitions for green

and sustainable supply chain management. Journal of Cleaner Production,

Vol. 52, 329–341.

Plambeck, Erica L. (2012) Reducing greenhouse gas emissions through operations and

supply chain management. Energy Economics, Vol. 34, 64–74.

Rajeev, A. – Pati, R. K. – Padhi, S. S. – Govindan, K. (2017) Evolution of sustainability

in supply chain management: A literature review. Journal of Cleaner Pro-

duction, Vol. 162, 299–314.

Rajnoha, R. – Lesníková, P. – Korauš, A. (2016) From Financial Measures to Strategic

Performance Measurement and Corporate Sustainability: Empirical Evi-

dence from Slovakia. Economics of Sociology, Vol. 9 (4), 134–152.

RobecoSAM (2018) DJSI index family. <https://www.sustainability-indices.com/index-

family-overview/djsi-index-family.html>, retrieved 4.10.2018.

RobecoSAM (2019) The SAM Corporate Sustainability Assessment.

<https://www.robecosam.com/csa/csa-resources/about-csa.html>, retrieved

10.3.2019.

Russell, Judith (2018) Beyond Sustainable: The Growing Demand for Ethical Fashion.

<https://www.therobinreport.com/beyond-sustainable-the-growing-de-

mand-for-ethical-fashion/>, retrieved 23.8.2018.

Sarkis, Joseph (1999) A methodological framework for evaluating environmentally con-

scious manufacturing programs. Computers & Industrial Engineering, Vol.

36, 793–810.

Sassen, R. – Hinze, A.-K. – Hardeck, I. (2016) Impact of ESG factors on firm risk in

Europe. Journal of Business Economics, Vol. 86 (8), 867–904.

Savitz, A. W. – Weber, K. (2006) The Triple Bottom Line: How Today's Best-Run Com-

panies Are Achieving Economic, Social and Environmental Success -- and

How You Can Too. 1st edition. Jossey-Bass, San Francisco.

Schmidt, C. G. – Förstl, K. – Schaltenbrand, B. (2017) The Supply Chain Position Para-

dox: Green Practices and Firm Performance. Journal of Supply Chain Man-

agement, Vol. 53 (1), 3–25.

Searcy, Cory (2012) Corporate Sustainability Performance Measurement Systems: A Re-

view and Research Agenda. Journal of Business Ethics, Vol. 107 (3), 239–

253.

Seles, B. M. R. P. – De Sousa Jabbour, A. B. L. – Jabbour, C. J. C. – Dangelico, R. M.

(2016) The green bullwhip effect, the diffusion of green supply chain prac-

tices and institutional pressures: Evidence from the automotive sector. In-

ternational Journal of Production Economics, Vol. 182, 342–355.

Seuring, S. – Müller, M. (2008) From a literature review to a conceptual framework for

sustainable supply chain management. Journal of Cleaner Production, Vol.

16 (15), 1699–1710.

83

Shen, Bin (2014) Sustainable Fashion Supply Chain: Lessons from H&M. Sustainability,

Vol. 6 (9), 6236–6249.

Siegel, Donald S. (2009) Green Management Matters Only If It Yields More Green: An

Economic/Strategic Perspective. Academy of Management Perspectives,

Vol. 23 (3), 5–16.

Singh, N. – Jain, S. – Sharma, P. (2016) Environmental benchmarking practices in Indian

industries: Evidences from an empirical study. Benchmarking: An Interna-

tional Journal, Vol. 23 (5), 1132–1146.

Slaper, T. F. – Hall, T. J. (2011) The Triple Bottom Line: What Is It and How Does It

Work? Indiana Business Review, 86 (1), 4–8.

Slavin, Terry (2018) Tim Mohin: ‘The world doesn’t need more CSR reports’. <http://eth-

icalcorp.com/tim-mohin-world-doesnt-need-more-csr-reports>, retrieved

4.10.2018.

Sloan, Thomas W. (2010) Measuring the Sustainability of Global Supply Chains: Current

Practices and Future Directions. Journal of Global Business Management,

Vol. 6 (1), 81–93.

Social Accountability International (2018) SA8000® Standard. <http://www.sa-

intl.org/index.cfm?fuseaction=Page.ViewPage&PageID=1689>, retrieved

29.10.2018.

Speziale, M.-T. – Klovienė, L. (2014) The relationship between performance measure-

ment and sustainability reporting: a literature review. Procedia - Social and

Behavioral Sciences, Vol. 156, 633–638.

Srivastava, Samir K. (2007) Green supply-chain management: A state-of-the-art literature

review. International Journal of Management Reviews, Vol. 9 (1), 53–80.

STOXX (2018) STOXX® Europe 600. <https://www.stoxx.com/index-details?sym-

bol=SXXP>, retrieved 25.8.2018.

Taborga, C. – Lusa, A. – Coves A. M. (2018) A Proposal for a Green Supply Chain Strat-

egy. Journal of Industrial Engineering and Management, Vol. 11 (3), 445–

465.

Tennant, Fraser (2015) The importance of corporate social responsibility. Financier

Worldwide Magazine November 2015.

The Economist (2002) Chain reaction. The Economist 2.2.2002. <https://www.econo-

mist.com/special-report/2002/01/31/chain-reaction>, retrieved 19.12.2018.

Thomson Reuters (2018) Thomson Reuters ESG Scores. <https://financial.thomsonreu-

ters.com/content/dam/openweb/documents/pdf/financial/esg-scores-meth-

odology.pdf>, retrieved 20.7.2018.

Touryalai, H. – Stoller, K. (2018) Global 2000: The World’s Largest Public Companies.

Forbes 6.6.2018. <https://www.forbes.com/global2000/#508e0222335d>,

retrieved 29.1.2019.

84

TRBC (2018) TRBC quick guide. <https://financial.thomsonreuters.com/con-

tent/dam/openweb/documents/pdf/financial/trbc-fact-sheet.pdf>, retrieved

25.8.2018.

Turker, D. – Altuntas, C. (2014) Sustainable supply chain management in the fast fashion

industry: An analysis of corporate reports. European Management Journal,

Vol. 32 (5), 837–849.

UNFCC (2018) Paris Agreement. <https://unfccc.int/process-and-meetings/the-paris-

agreement/the-paris-agreement>, retrieved 20.7.2018.

UNIDO (2018) What is CSR? <https://www.unido.org/our-focus/advancing-economic-

competitiveness/competitive-trade-capacities-and-corporate-responsibil-

ity/corporate-social-responsibility-market-integration/what-csr>, retrieved

24.7.2018.

United Nations Global Compact (2018) Our Mission. <https://www.unglobalcom-

pact.org/what-is-gc/mission>, retrieved 21.2.2019.

Vafidis, Dimitrios (2007) Approaches for knowledge and application creation in logis-

tics. Publications of Turku School of Economics A-3:2007.

Van der Leeuw, S. – Wiek, A. – Harlow, J. – Buizer, J. (2012) How much time do we

have? Urgency and rhetoric in sustainability science. Sustainability Science,

Vol. 7 (Supplement 1), 115–120.

Van Tulder, R. – Wijk, J. – Kolk, A. (2009) From Chain Liability to Chain Responsibility.

Journal of Business Ethics, Vol. 85 (Supplement 2), 399–412.

Villena, V. H. – Gioia, D. A. (2018) On the riskiness of lower-tier suppliers: Managing

sustainability in supply networks. Journal of Operations Management, Vol.

64, 65–87.

Walter, A. – Dolzan, P. – Quilodrán, O. – De Oliveira, J. G. – De Silva, C. – Piacente, F.

– Segerstedt, A. (2011) Sustainability assessment of bio-ethanol production

in Brazil considering land use change, GHG emissions and socio-economic

aspects. Energy Policy, Vol. 39 (10), 5703–5716.

Wamsley, Laurel (2018) California Judge Cuts Award To $78.5 Million In Monsanto

Weedkiller Case. <https://www.npr.org/2018/10/23/659848853/california-

judge-cuts-award-to-78-5-million-in-monsanto-weedkiller-

case?t=1557826612539>, retrieved 14.5.2019.

Wang, X. – Disney, S. M. (2016) The bullwhip effect: Progress, trends and directions.

European Journal of Operational Research, Vol. 250, 691–701.

White, Jeremy B. (2017) Nestle has been bottling and selling water it has no right to in

drought-stricken California, state says. Independent 27.12.2017.

<https://www.independent.co.uk/news/world/americas/nestle-water-sell-

ing-diverting-bottled-arrowhead-san-bernardino-forest-california-

a8130686.html>, retrieved 23.8.2018.

85

Wilhelm, M. M. – Blome, C. – Bhakoo, V. – Paulraj, A. (2016) Sustainability in multi-

tier supply chains Understanding the double agency role of the first-tier sup-

plier. Journal of Operations Management, Vol. 41, 42–60.

Willis, M. M. – Schor, J. B. (2012) Does Changing a Light Bulb Lead to Changing the

World? Political Action and the Conscious Consumer. The Annals of the

American Academy of Political and Social Science, Vol. 644, 160–190.

Willuhn, Marian (2018) World reacts to IPCC report. <https://www.pv-maga-

zine.com/2018/10/09/world-reacts-to-ipcc-report/>, retrieved 6.10.2018.

Wolf, Julia (2014) The Relationship Between Sustainable Supply Chain Management,

Stakeholder Pressure and Corporate Sustainability Performance. Journal of

Business Ethics, Vol. 119 (3), 317–328.

Wu, Z. – Pagell, M. (2011) Balancing priorities: Decision-making in sustainable supply

chain management. Journal of Operations Management, Vol. 29, 577–590.

Wynstra, F. – Von Corswant, F. – Wetzels, M. (2010) In Chains? An Empirical Study of

Antecedents of Supplier Product Development Activity in the Automotive

Industry. Journal of Product Innovation Management, Vol. 27 (5), 625–639.

Yakovleva, N. – Sarkis, J. – Sloan, T. (2012) Sustainable benchmarking of supply chains:

The case of the food industry. International Journal of Production Re-

search, Vol. 50 (5), 1297–1317.

Yarime, M. – Trencher, G. – Mino, T. – Scholz, R. W. – Olsson, L. – Ness, B. – Fran-

tzeskaki, N. – Rotmans, J. (2012) Establishing sustainability science in

higher education institutions: Towards an integration of academic develop-

ment, institutionalization, and stakeholder collaborations. Sustainability

Science, Vol. 7 (Supplement 1), 101–113.

Yawar, S. A. – Seuring, S. (2017) Management of Social Issues in Supply Chains: A

Literature Review Exploring Social Issues, Actions and Performance Out-

comes. Journal of Business Ethics, Vol 141 (3), 621–643.

Zhang, B. – Bi, J. – Fan, Z. – Yuan, Z. – Ge, J. (2008) Eco-efficiency analysis of industrial

system in China: A data envelopment analysis approach. Ecological Eco-

nomics, Vol. 68 (1–2), 306–316.

Zhou, Y. – Bao, M. – Xiaohong, C. – Xuanhua, X. (2016) Co-op advertising and emission

reduction cost sharing contracts and coordination in low-carbon supply

chain based on fairness concerns. Journal of Cleaner Production, Vol. 133,

402–413.

Zhu, Q. – Sarkis, J. – Lai, K. (2012) Examining the effects of green supply chain man-

agement practices and their mediations on performance improvements. In-

ternational Journal of Production Research, Vol. 50 (5), 1377–1394.

86

APPENDIX 1 ESG ENVIRONMENTAL MEASURES LIST

Environmental pillar (97 measures in total)

Resource Use category (31)

Resource Reduction Policy

Policy Water Efficiency

Policy Energy Efficiency

Policy Sustainable Packaging

Policy Environmental Supply Chain

Resource Reduction Targets

Targets Water Efficiency

Targets Energy Efficiency

Environment Management Team

Environment Management Training

Environmental Materials Sourcing

Toxic Chemicals Reduction

Total Energy Use/Million in Revenue (USD)

Renewable Energy Use Ratio

Energy Use Total

Energy Purchased Direct

Energy Produced Direct

Electricity Purchased

Electricity Produced

Renewable Energy Purchased

Renewable Energy Produced

Renewable Energy Use

Green Buildings

Total Water Use/Million in Revenue (USD)

Water Withdrawal Total

Fresh Water Withdrawal Total

Environmental Supply Chain Management

Environmental Supply Chain Monitoring

Env Supply Chain Partnership Termination

Land Environmental Impact Reduction

Environmental Controversies

87

Environmental pillar (97 measures in total)

Emissions category (41)

Policy Emissions

Targets Emissions

Biodiversity Impact Reduction

Total CO2 Emissions/Million in Revenue (USD)

CO2 Equivalent Emissions Total

CO2 Equivalent Emissions Direct, Scope 1

CO2 Equivalent Emissions Direct, Scope 2

CO2 Equivalent Emissions Direct, Scope 3

Carbon Offsets/Credits

Estimated CO2 Equivalents Emission Total

CO2 Estimation Method

Emissions Trading

Climate Change Commercial Risks Opportunities

Nox and Sox Emissions Reduction

Nox Emissions

Sox Emissions

VOC or Particulate Matter Emissions Reduction

VOC Emissions Reduction

Particulate Matter Emissions Reduction

VOC Emissions

Total Waste/Million in Revenue (USD)

Waste Recycled To Total Waste

Total Hazardous Waste/Million in Revenue (USD)

Waste Total

Non-Hazardous Waste

Waste Recycled Total

Waste Recycling Ratio

Hazardous Waste

Waste Reduction Initiatives

e-Waste Reduction

Total Water Pollutant Emissions/

Million in Revenue (USD)

Water Discharged

Water Pollutant Emissions

ISO 14000 or EMS

EMS Certified Percent

Environmental Restoration Initiatives

Staff Transportation Impact Reduction

Environmental Expenditures Investments

Environmental Expenditures

Environmental Investments Initiatives

Environmental Partnerships

88

Environmental pillar (97 measures in total)

Innovations category (25)

Environmental Products

Eco-Design Products

Total Environmental R&D (USD)/

Million in Revenue (USD)

Noise Reduction

Fleet Fuel Consumption

Hybrid Vehicles

Fleet CO2 Emissions

Environmental Assets Under Management

Equator Principles

Environmental Project Financing

Nuclear

Labelled Wood

Organic Products Initiatives

Product Impact Minimisation

Take-back and Recycling Initiatives

Product Environmental Responsible Use

GMO Products

Agrochemical Products

Agrochemical 5 % Revenue

Animal Testing

Animal Testing Cosmetics

Animal Testing Reduction

Renewable/Clean Energy Products

Water Technologies

Sustainable Building Products

89

APPENDIX 2 ESG SOCIAL MEASURES LIST

Social pillar (105 measures in total)

Workforce category (47)

Health & Safety Policy

Policy Employee Health & Safety

Policy Supply Chain Health & Safety

Training and Development Policy

Policy Skills Training

Policy Career Development

Policy Diversity and Opportunity

Targets Diversity and Opportunity

Employees Health & Safety Team

Health & Safety Training

Supply Chain Health & Safety Training

Employees Health & Safety OHSAS 18001

Employee Satisfaction

Salary Gap

Salaries and Wages From CSR Reporting

Net Employment Creation

Number of Employees from CSR Reporting

Trade Union Representation

Turnover of Employees

Announced Layoffs To Total Employees

Announced Layoffs

Strikes

Women Employees

Women Managers

Flexible Working Hours

Day Care Services

Employees With Disabilities

Injuries to Million Hours

Total Injury Rate Total

Total Injury Rate Employees

Accidents Total

Employee Accidents

Employee Fatalities

Lost Days/Million Working Days

Lost Time Injury Rate Total

Lost Time Injury Rate Employees

Lost Working Days

Employee Lost Working Days

HIV-AIDS Programme

90

Social pillar (105 measures in total)

Workforce category (47)

Average Training Hours

Training Hours Total

Training Costs Total

Training Costs Per Employee

Internal Promotion

Management Training

Supplier ESG Training

Wages Working Condition Controversies

Social pillar (105 measures in total)

Human Rights category (9)

Human Rights Policy

Policy Freedom of Association

Policy Child Labour

Policy Forced Labour

Policy Human Rights

Fundamental Human Rights ILO UN

Human Rights Contractor

Ethical Trading Initiative ETI

Human Rights Breaches Contractor

Community category (21)

Policy Fair Competition

Policy Bribery and Corruption

Policy Business Ethics

Policy Community Involvement

Improvement Tools Business Ethics

OECD Guidelines for Multinational Enterprises

Extractive Industries Transparency Initiative

Total Donations/Million in Revenue (USD)

Donations Total

Political Contributions

Lobbying Contribution Amount

Employee Engagement Voluntary Work

Corporate Responsibility Awards

Product Sales at Discount to Emerging Markets

Diseases of the Developing World

Bribery, Corruption and Fraud Controversies

Crisis Management Systems

Anti-Competition Controversies

Critical Country 1

Critical Country 2

Critical Country 3

91

Social pillar (105 measures in total)

Product Responsibility category (28)

Policy Customer Health & Safety

Policy Data Privacy

Policy Responsible Marketing

Policy Fair Trade

Product Responsibility Monitoring

Quality Management Systems

ISO 9000

Six Sigma and Quality Management Systems

QMS Certified Percent

Customer Satisfaction

Product Access Low Price

Healthy Food or Products

Embryonic Stem Cell Research

Retailing Responsibility

Alcohol

Gambling

Tobacco

Armaments

Pornography

Contraceptives

Obesity Risk

Cluster Bombs

Anti-Personal Landmines

Consumer Complaints Controversies

Product Quality Controversies

Responsible Marketing Controversies

Product Delays

Product Recall

92

APPENDIX 3 SAMPLE COMPANIES, MANUFACTURER 1 SCP

Company Thomson Reuters Business

Classification Activity Industry

A2A Renewable Utilities P

Aalberts Industries Industrial Machinery & Equipment (NEC) Ma

AB SKF Industrial Machinery & Equipment (NEC) Ma

ABB Heavy Electrical Equipment (NEC) Ma

Aggreko Business Support Services (NEC) Ma

Air Liquide Commodity Chemicals (NEC) P

Aker BP Oil & Gas Exploration and Production

(NEC) P

AkzoNobel Paints & Coatings P

Alfa Laval Industrial Machinery & Equipment (NEC) Ma

Alstom Heavy Machinery & Vehicles (NEC) Ma

ams AG Semiconductors (NEC) C

Anglo American Diversified Mining Me

Antofagasta Copper Ore Mining Me

ArcelorMittal Iron & Steel (NEC) Me

Arkema Commodity Chemicals (NEC) P

ASML Holdiing Semiconductor Equipment & Testing (NEC) C

Atlas Copco A Industrial Machinery & Equipment (NEC) Ma

BASF Diversified Chemicals P

BE Semiconductor Semiconductor Machinery Manufacturing C

BHP Billiton Diversified Mining Me

BillerudKorsnäs Paper Packaging (NEC) L

Boliden Specialty Mining & Metals (NEC) Me

BP Oil & Gas Refining and Marketing (NEC) P

CEZ Electric Utilities (NEC) P

Chr. Hansen Holding Food Ingredients P

Clariant Specialty Chemicals (NEC) P

Continental Auto, Truck & Motorcycle Parts (NEC) Ma

Covestro Plastics L

CRH Construction Materials (NEC) L

Croda International Specialty Chemicals (NEC) P

DS Smith Paper Packaging (NEC) L

EDF Multiline Utilities P

Ems-Chemie Holding Commodity Chemicals (NEC) P

Endesa Electric Utilities (NEC) P

ENGIE Multiline Utilities P

Eni Integrated Oil & Gas P

Equinor Integrated Oil & Gas P

Evonik Industries Diversified Chemicals P

EVRAZ Iron, Steel Mills & Foundries Me

Faurecia Auto, Truck & Motorcycle Parts (NEC) Ma

93

Company Thomson Reuters Business

Classification Activity Industry

Fortum Electric Utilities (NEC) P

Fresnillo Diversified Mining Me

FUCHS PETROLUB SE Commodity Chemicals (NEC) P

Galp Energia Oil & Gas Refining and Marketing (NEC) P

Geberit Plumbing Fixtures & Fittings L

Georg Fischer Industrial Machinery & Equipment (NEC) Ma

Givaudan Commodity Chemicals (NEC) P

Glencore Plc Coal (NEC) P

Halma Electrical Components & Equipment (NEC) C

HeidelbergCement Construction Materials (NEC) L

Henkel AG & Co. KGaA Adhesives P

Hexagon B Electronic Equipment & Parts (NEC) C

HEXPOL AB Advanced Polymers P

Iberdrola Electric Utilities (NEC) P

Imerys Diversified Chemicals P

IMI plc Industrial Machinery & Equipment (NEC) Ma

Infineon Technologies Semiconductors (NEC) C

K + S Agricultural Chemicals (NEC) P

KAZ Minerals PLC Diversified Mining Me

Koninklijke DSM NV Diversified Chemicals P

LafargeHolcim Cement & Concrete Manufacturing L

LANXESS Diversified Chemicals P

Legrand Electrical Components & Equipment (NEC) C

Linde AG Industrial Gases P

Lonza Biotechnology & Medical Research (NEC) P

Lundin Petroleum Oil & Gas Exploration and Production

(NEC) P

Meggit PLC Aircraft Parts Manufacturing Ma

Michelin Tires & Rubber Products (NEC) L

Mondi Paper Packaging (NEC) L

MTU Aero Engines Aircraft Parts Manufacturing Ma

Neste Oil & Gas Refining and Marketing (NEC) P

NIBE Industrier AB Heating, Ventilation & Air Conditioning

Systems L

Nokian Renkaat Tires & Rubber Products (NEC) L

Norsk Hydro Aluminum (NEC) Me

Novozymes Commodity Chemicals (NEC) P

OC Oerlikon Industrial Machinery & Equipment (NEC) Ma

OMV Oil & Gas Refining and Marketing (NEC) P

OSRAM Licht AG Lighting Equipment L

Pirelli & C. S.p.A. Tire & Tube Manufacturers L

Plastic Omnium Automotive Body Parts Ma

Polymetal International Diversified Mining Me

Prysmian Wires & Cables C

94

Company Thomson Reuters Business

Classification Activity Industry

Randgold Resources Gold (NEC) Me

Repsol Oil & Gas Refining and Marketing (NEC) P

Rexel Electrical Components & Equipment (NEC) C

Rheinmetall Engine & Powertrain Systems Ma

Rio Tinto Diversified Mining Me

Rockwool International A/S Construction Supplies L

Rotork Fluid Power Cylinder & Actuators Ma

Royal Dutch Shell plc Integrated Oil & Gas P

RPC Group Plc Plastic Containers & Packaging L

Safran Aircraft Parts Manufacturing Ma

Saint-Gobain Construction Supplies & Fixtures (NEC) L

Sandvik Industrial Machinery & Equipment (NEC) Ma

Schaeffler AG Auto, Truck & Motorcycle Parts (NEC) Ma

Schindler Elevator & Conveying Equipment Ma

Schneider Electric Electrical Components & Equipment (NEC) C

Sika Specialty Chemicals (NEC) P

Siltronic AG Semiconductors (NEC) C

Smurfit Kappa Group Paper Packaging (NEC) L

Solvay Commodity Chemicals (NEC) P

Spectris Electrical Components & Equipment (NEC) C

Spirax-Sarco Engineering

plc Industrial Machinery & Equipment (NEC) Ma

STMicroelectronics Semiconductors (NEC) C

Stora Enso Oyj Paper Products (NEC) L

Svenska Cellulosa (SCA)

AB Paper Products (NEC) L

Symrise Specialty Chemicals (NEC) P

Tate & Lyle Food Ingredients P

Tenaris Oil Related Equipment L

ThyssenKrupp Iron & Steel (NEC) Me

Total Integrated Oil & Gas P

Trelleborg AB Specialty Chemicals (NEC) P

Tullow Oil Oil & Gas Exploration and Production

(NEC) P

Umicore Waste Management, Disposal &

Recycling Services P

UPM-Kymmene Paper Products (NEC) P

Valeo Auto, Truck & Motorcycle Parts (NEC) Ma

VAT Group AG Industrial Valve Manufacturing L

Victrex Specialty Chemicals (NEC) P

Wienerberger Construction Materials (NEC) L

Viscofan Non-Paper Containers & Packaging (NEC) L

Voestalpine Iron & Steel (NEC) Me

Wärtsila Industrial Conglomerates Ma

Yara International ASA Agricultural Chemicals (NEC) P

95

Company Thomson Reuters Business

Classification Activity Industry

UPM-Kymmene Paper Products (NEC) P

Valeo Auto, Truck & Motorcycle Parts (NEC) Ma

VAT Group AG Industrial Valve Manufacturing L

Victrex Specialty Chemicals (NEC) P

Wienerberger Construction Materials (NEC) L

Viscofan Non-Paper Containers & Packaging (NEC) L

Voestalpine Iron & Steel (NEC) Me

Wärtsila Industrial Conglomerates Ma

Yara International ASA Agricultural Chemicals (NEC) P

Note Industry abbreviations used in the appendix:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

96

APPENDIX 4 SAMPLE COMPANIES, MANUFACTURER 2 SCP

Company Thomson Reuters Busines

Classification Activity Industry

Adidas Sports & Outdoor Footwear L

Airbus Commercial Aircraft Manufacturing Ma

Ambu Medical Equipment, Supplies & Distribution

(NEC) C

Amer Sports Sporting & Outdoor Goods L

Andritz Industrial Machinery & Equipment (NEC) Ma

Anheuser-Busch InBev Brewers (NEC) P

Assa Abloy Construction Supplies & Fixtures (NEC) L

Associated British Foods Food Processing (NEC) P

BAE Systems Aerospace & Defense (NEC) Ma

Barry Callebaut Chocolate & Confectionery P

Bayer Pharmaceuticals (NEC) P

Beiersdorf Personal Products (NEC) L

BIC Business Support Supplies (NEC) L

BMW Auto & Truck Manufacturers (NEC) Ma

British American Tobacco Tobacco (NEC) P

Britvic Non-Alcoholic Beverages (NEC) P

BTG PLC Pharmaceuticals (NEC) P

Bucher Industries Heavy Machinery & Vehicles (NEC) Ma

Carlsberg A/S Brewers (NEC) P

Christian Dior SE Apparel & Accessories (NEC) L

CNH Industrial N.V. Heavy Machinery & Vehicles (NEC) Ma

Cobham plc Aerospace & Defense (NEC) Ma

Coca-Cola Hbc Non-Alcoholic Beverages (NEC) P

Compagnie Financière

Richemont SA Jewelry Me

ConvaTec Proprietary & Advanced Pharmaceuticals P

Daimler Auto & Truck Manufacturers (NEC) Ma

Danone Food Processing (NEC) P

Dassault Aviation Commercial Aircraft Manufacturing Ma

Davide Campari-Milano

S.p.A. Distillers & Wineries (NEC) P

Dechra Pharmaceuticals Veterinary Drugs P

Diageo Distillers & Wineries (NEC) P

dormakaba Holding AG Security & Surveillance C

Dúrr AG Industrial Machinery & Equipment (NEC) Ma

Electrolux AB Appliances, Tools & Housewares (NEC) L

Epiroc AB Heavy Machinery & Vehicles (NEC) Ma

F. Hoffmann-La Roche AG Pharmaceuticals (NEC) P

Ferrari N.V. Automobiles & Multi Utility Vehicles Ma

Fiat Chrysler Automobiles Automobiles & Multi Utility Vehicles Ma

97

Company Thomson Reuters Business

Classification Activity Industry

Fresenius Medical Care AG Healthcare Facilities & Services (NEC) P

GEA Group Industrial Machinery & Equipment (NEC) Ma

Getinge AB Medical Equipment L

Glanbia Plc Dairy Products P

GN Store Nord Advanced Medical Equipment &

Technology (NEC) C

Grifols Biopharmaceuticals P

Groupe SEB Appliances, Tools & Housewares (NEC) Ma

H & M Hennes &

Mauritz AB Apparel & Accessories (NEC) L

H. Lundbeck A/S Pharmaceuticals (NEC) P

Heineken N.V. Brewers (NEC) P

Howden Joinery Group plc Home Furnishings (NEC) L

Hugo Boss AG Apparel & Accessories (NEC) L

Huhtamäki Oyj Paper Packaging (NEC) L

Husqvarna AB Appliances, Tools & Housewares (NEC) L

Imperial Brands Tobacco (NEC) P

Indivior Proprietary & Advanced Pharmaceuticals P

Ipsen Pharmaceuticals (NEC) P

Johnson Matthey Specialty Chemicals (NEC) P

Kerry Group Fruit & Vegetable Processing P

Kingspan Group Flooring & Interior Tile Manufacturers L

KION Group Heavy Machinery & Vehicles (NEC) Ma

KONE Oyj Elevator & Conveying Equipment Ma

Konecranes Heavy Machinery & Vehicles (NEC) Ma

Leonardo S.p.A. Aerospace & Defense (NEC) Ma

Lindt & Sprüngli Chocolate & Confectionery P

Logitech International S.A. Computer Hardware (NEC) C

L'Oreal S.A. Cosmetics & Perfumes L

LVMH Moët Hennessy

Louis Vuitton SE Apparel & Accessories (NEC) L

Marine Harvest Food Processing (NEC) P

Merck KGaA Proprietary & Advanced Pharmaceuticals P

Metso Oyj Industrial Machinery & Equipment (NEC) Ma

Nestlé Food Processing (NEC) P

Novartis Pharmaceuticals (NEC) P

Novo Nordisk Pharmaceuticals (NEC) P

Orion Pharmaceuticals (NEC) P

Orkla Food Processing (NEC) P

Pandora Jewelry Me

Pernod Ricard Distillers & Wineries (NEC) P

Peugeot Auto & Truck Manufacturers (NEC) Ma

Philips Advanced Medical Equipment &

Technology (NEC) L

98

Company Thomson Reuters Business

Classification Activity Industry

Porsche Automobil

Holding SE Auto & Truck Manufacturers (NEC) Ma

Reckitt Benckiser Personal Products (NEC) L

Recordati Pharmaceuticals (NEC) P

Remy Cointreau Distillers & Wineries (NEC) P

Renault Auto & Truck Manufacturers (NEC) Ma

Rolls-Royce Holdings Aerospace & Defense (NEC) Ma

Saab AB Aerospace & Defense (NEC) Ma

Shire Pharmaceuticals (NEC) P

Siemens AB Industrial Conglomerates C

Siemens Gamesa Wind Systems & Equipment Ma

Signify Lighting Fixtures L

Smiths Group Industrial Conglomerates L

Sonova Holding AG Medical Prosthetics C

Straumann Medical Prosthetics C

Swatch Group Watches L

Swedish Match Tobacco (NEC) P

Tecan Group AG Scientific & Precision Equipment C

Thales Group Satellite Design & Manufacture C

UCB S.A. Pharmaceuticals (NEC) P

Unilever N.V. Personal Products (NEC) L

Unilever plc Personal Products (NEC) L

Vestas Wind Systems A/S Wind Systems & Equipment Ma

Volkswagen AG Auto & Truck Manufacturers (NEC) Ma

Volvo AB Heavy Trucks Ma

Note Industry abbreviations used in the appendix:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics

99

APPENDIX 5 SAMPLE COMPANIES, VENDOR SCP

Company Thomson Reuters Business

Classification Activity Industry

Ahold Delhaize Food Retail & Distribution (NEC) P

ASOS plc Apparel & Accessories Retailers (NEC) L

Axfood AB Supermarkets & Convenience Stores P

B&M European Value

Retail S.A. Discount Stores (NEC) P

Bergman & Beving AB Industrial Machinery & Equipment

Wholesale Ma

Brenntag AG Diversified Chemicals P

Bunzl plc Diversified Industrial Goods Wholesalers L

Burberry Group PLC Apparel & Accessories Retailers (NEC) L

Card Factory plc Gift, Novelty & Souvenir Stores L

CCC S.A. Footwear Retailers L

CECONOMY AG Computer & Electronics Retailers (NEC) C

Clas Ohlson AB Home Improvement Products & Services

Retailers (NEC) L

Coloplast A/S Medical Equipment Wholesale L

Debenhams Plc Department Stores (NEC) L

D'Ieteren SA Auto Vehicles, Parts & Service Retailers

(NEC) Ma

Dino Polska S.A. Supermarkets & Convenience Stores P

Diploma plc Industrial Machinery & Equipment

Wholesale Ma

Dixons Carphone plc Computer & Electronics Retailers (NEC) C

Dufry AG Miscellaneous Specialty Retailers (NEC) L

Dunelm Group plc Home Furnishings Retailers (NEC) L

Electrocomponents plc Electric Equipment Wholesale C

Etablissementen Franz

Colruyt NV Food Retail & Distribution (NEC) P

Eurocash S.A. Food Retail & Distribution (NEC) P

Ferguson plc Construction Supplies & Fixtures Wholesale L

Fielmann AG Optical Goods Stores L

Findel plc Internet & Mail Order Department Stores L

Galenica AG Retail - Drugs without Grocery P

Grafton Group plc Construction Material Wholesale L

GrandVision N.V. Optical Goods Stores L

Hermes International SCA Handbags & Luggage L

Ica Gruppen AB Supermarkets & Convenience Stores P

IMCD Specialty Chemicals Wholesale P

Inchcape plc Auto Vehicles, Parts & Service Retailers

(NEC) Ma

100

Company Thomson Reuters Business

Classification Activity Industry

Industria de Diseño

Textil S.A. Apparel & Accessories Retailers (NEC) L

J Sainsbury plc Supermarkets & Convenience Stores P

JD Sports Fashion Plc Sports & Outdoors Retailers L

Jerónimo Martins Food Retail & Distribution (NEC) P

Jumbo S.A. Miscellaneous Specialty Retailers (NEC) L

Kering Apparel & Accessories Retailers (NEC) L

Kesko Supermarkets & Convenience Stores P

Kingfisher plc Home Improvement Products & Services

Retailers (NEC) L

Lookers plc New Car Dealers Ma

Luxottica Group Optical Goods Stores L

Magnit PAO Food Retail & Distribution (NEC) P

Marks & Spencer Group plc Miscellaneous Specialty Retailers (NEC) P

McKesson Europe AG Drug Retailers (NEC) P

Mekonomen AB Automotive Parts & Accessories Retailers Ma

Metro AG Food Retail & Distribution (NEC) P

Moncler Apparel & Accessories (NEC) L

N Brown Group plc Apparel & Accessories Retailers (NEC) L

Next PLC Miscellaneous Specialty Retailers (NEC) L

Ocado Internet & Mail Order Discount Stores P

Pets at Home Group Plc Pet & Pet Supplies Retailers P

Rubis Petroleum Product Wholesale P

SIG plc Construction Supplies & Fixtures Wholesale L

Sports Direct

International plc Sporting Goods Stores L

Superdry PLC Apparel & Accessories Retailers (NEC) L

Ted Baker PLC Apparel & Accessories Retailers (NEC) L

Tesco plc Food Retail & Distribution (NEC) P

Travis Perkins plc Builder Merchants L

Valora Holding AG Miscellaneous Specialty Retailers (NEC) P

WHSmith plc Book & Magazine Retailers P

Vifor Pharma Pharmaceuticals (NEC) P

Wm Morrison

Supermarkets plc Food Retail & Distribution (NEC) P

Zalando Apparel & Accessories Retailers (NEC) L

Note Industry abbreviations used in the appendix:

P Process industry

L Light industry

Me Metal refining and metal productions

Ma Appliances, machines and transport equipment

C Computers and electronics